# Dielectric constant of disordered phases of the smallest monoalcohols :
evidence for the hindered plastic crystal phase.

M.V.Kondrin<EMAIL_ADDRESS>Institute for High Pressure Physics RAS,
108840 Troitsk, Moscow, Russia  A.A. Pronin  General Physics Institute RAS,
117942 Moscow, Russia  Y.B. Lebed  Institute for Nuclear Research RAS, 117312
Moscow, Russia  V.V. Brazhkin  Institute for High Pressure Physics RAS, 108840
Troitsk, Moscow, Russia

###### Abstract

With gradual temperature increase in premelting regions of solid phase of
methanol and high pressure phase of ethanol, and using novel procedure of
separation of electrode polarization effects, we are able to register the
contribution of relaxation process to low-frequency dielectric constant. This
contribution is about half the liquid’s dielectric constant near temperature
of solidification , and is almost an order of magnitude higher than reported
earlier for ambient pressure phase of methanol. As opposed to dielectric
constant of water at ambient pressure, which does not change much during
crystallization, our finding indicates the hindrance of molecule rotation in
orientationally disordered phases of monoalcohols. Similar dielectric
responses of ambient pressure methanol and high-pressure phase of ethanol
imply existence of hindered plastic crystal phase of ethanol (not observed at
low pressures). We also have found some dynamic disorder in nominally fully
ordered phase of these monoalcohols ($\alpha$-phase of methanol and low-
pressure phase of ethanol), the contribution of this disorder being dependent
on external conditions (e.g. temperature), and increasing at approaching the
order-disorder transition. On the other hand, the amplitude of dielectric
responce in hindered plastic crystal phases is almost independent of
temperature.

##  I Introduction

The concept of plastic crystal was first introduced by Timmermans almost
hundred years ago Timmermans (1961). It was based on observation, that some
molecular crystals with almost globular molecular structure have melting
entropy lower than 5 cal/ K mole (20.92 J/K mole). This implies that some
thermodynamic degrees of freedom (predominantly rotational ones) are already
activated in solid phase, thus leading to reduced value of fusion entropy. It
was postulated, that high-temperature solid phases of these substances just
below the melting curve consist of orientationally disordered molecules, which
can freely rotate around translationally ordered positions. Translationally
ordered, but orientationally disordered crystal phase was named plastic
crystal. Thermodynamic criterion of plastic crystals was chosen slightly
arbitrary, thus, for example, ordinary ice with fusion entropy of 21.97 J/ K
mole, with hydrogen bonds disorder, does not belong to them. However,
thermodynamic notion clearly discerns between molecular substances in which
orientational disorder at increase of temperature precedes the onset of
translational one (melting).

\begin{overpic}[width=433.62pt]{PTfig3-meoh.pdf} \put(100.0,730.0){{\Large
a)}} \put(650.0,150.0){\includegraphics[width=108.405pt]{meoh.png}}
\end{overpic}\begin{overpic}[width=433.62pt]{ethanol-pt2.pdf}
\put(100.0,730.0){{\Large b)}}
\put(650.0,150.0){\includegraphics[width=108.405pt]{etoh.png}} \end{overpic}

Figure 1: a) Phase diagram of methanol according to Kondrin et al. Kondrin
_et al._ (2013). $\beta$-phase corresponds to orientationally disordered
methanol phase. b) Phase diagram of ethanol according to Kondrin et al.
Kondrin  _et al._ (2014). In insets the respective molecules of monoalcohols
are shown.

Crystallographic investigations are more definite and can discern between
various types of disorder. While orientational disorder in hexagonal ice
persists from 273 K down to helium temperature, orientationally disordered
methanol ($\beta$-phase) exists in quite limited temperature range – from
175.5 K to 160 K. Moreover, the model predicts different types of disorder in
ice and methanol. In ice, hydrogen bonds can switch between four positions in
tetrahedrally bonded hexagonal crystal Onsager and Runnels (1969); Ryzhkin
_et al._ (2020), while, in $\beta$-phase of methanol, hydrogen bonds have
linear structure (plastic crystal of methanol has anisotropic orthorhombic
structure with $Cmcm$ space group Tauer and Lipscomb (1952); Allan  _et al._
(1998); Torrie  _et al._ (1989, 2002) in contrast to highly symmetric
hexagonal ice) and can be switched between two positions only. It implies
different degrees of hindrance of molecules’ free rotation in the phase of
plastic crystal. Crystallographic studies reveal disorder of hydrogen atoms in
$\beta$-phase of solid methanol, while C-O axis direction being fixed Tauer
and Lipscomb (1952); Allan  _et al._ (1998); Torrie  _et al._ (1989, 2002).
The remnant of this linear ordering in monoalcohols persists even in the
liquid phase which results in difference between characteristic time of
dielectric response and structural relaxation Gainaru  _et al._ (2010); Böhmer
_et al._ (2014). In ordinary ice, on the contrary, only oxygen position is
fixed, and the pair of protons can freely select between four bonds with
nearby oxygen atoms (so called Bjerrum fault) Onsager and Runnels (1969);
Ryzhkin  _et al._ (2020). Previous dielectric spectroscopy studies have shown
that disordered phase of methanol exists till very high pressures ($P<$ 6 GPa,
see Fig. 2 a) Kondrin  _et al._ (2013), while in ice the pressure increase
results in exceptionally rich phase diagram which includes
crystallographically different proton ordered and disordered phases. In case
of methanol theoretical studies (classical molecular dynamics Gonzalez-Salgado
and Vega (2016) and ab-initio crystal structure prediction Červinka and Beran
(2018)) are of little help, because although they describe more or less
precisely the stability region of ordered methanol phases ($\alpha$ and
$\gamma$), but both unanimously predict metastability of orientationally
disordered $\beta$-phase , which contradicts experimental observations.

Since hydrogen bond has large dipole moment, the difference in crystal
structures (and accompanying disorder) would greatly influence the value of
dielectric constant Onsager and Runnels (1969). Static dielectric constant is
sensitive to fluctuations of molecular dipole moment, so with the switches of
molecular dipoles its value would be large, while in frozen molecules only
induced polarization ( an order of magnitude weaker) can contribute to
dielectric response (thus leading to low values of dielectric permittivity).
In liquid water at 273 K dielectric constant is equal to 81 and slightly
increases in solid phase Ellison (2007); Johari and Whalley (1981). This
implies that almost free rotation of molecular dipoles is practically retained
in solid phase. On the other hand, dielectric constant of liquid methanol
phase is equal to $\approx$ 75 near the melting point, but strongly decreases
during crystallization (down to 4-6) Denney and Cole (1955); Davidson (1957);
Kondrin  _et al._ (2013). This implies strong hindrance of free rotation in
plastic crystal phase of solid methanol, which is not compatible with
crystallographic evidence of almost free rotation of methanol molecules around
C-O bond Tauer and Lipscomb (1952); Allan  _et al._ (1998); Torrie  _et al._
(1989, 2002). We argue, that static dielectric constant of methanol in the
disordered $\beta$ phase is significantly larger, but corresponds to the low
frequency relaxation process, so it almost merges with effects caused by
contact polarization processes. Still, in premelting region, we are able to
separate these two types of processes. Comparison of obtained dielectric
spectroscopy data for methanol with high pressure data obtained for another
small-molecule monoalcohol, ethanol, enables us to suggest the existence of
orientationally disordered crystal phase in ethanol at high pressures.

##  II Methods

Dielectric spectroscopy measurements of ethanol and methanol at ultra-high
pressures were carried out in Toroid chamber Khvostantsev  _et al._
(2004)according to routine, reported earlier Pronin  _et al._ (2010a, b);
Kondrin  _et al._ (2012). Experimentally accessible frequency window (10 Hz –
2 MHz) and precision of dielectric susceptibility measurements
($\Delta\varepsilon\approx 0.1$) were determined using QuadTech-7600qua
(1997)device . The values of capacitance were measured twice before an
experiment , in empty and filled capacitor, and subsequently used for
calculation of dielectric susceptibility at high pressure. “Empty” capacitance
readings were about 10 pF. During high-pressure experiments, variation of
thermodynamic parameters in crystal phase was possible only along isobars
(with typical rate $\pm 0.5$ K/min), because otherwise the pressure change
would lead to the breakage of the measurement capacitors. The pressure values
during experiments were estimated by the readings of manganin gauge in liquid
phase , just prior to the crystallization onset, with typical accuracy of
$\pm$ 0.05 GPa. The rate of temperature variation was not strictly controlled,
mostly it was determined by the thermal inertia (quite large) of our setup.
Typical cooling rate was about $-0.5$ K/min, but heating rate could vary in
the range $0.5-1$ K/min by application of external manual heating. The
temperature of the measurement cell was controlled by alumel-chromel
thermocouple with precision of 0.01 K. The results presented were obtained in
several high-pressure experiments with different measurement cells. Ambient
pressure measurement was carried out using controlled heating/cooling setup
and was effectuated with the rate $\pm$ 0.01 K/s. The data eported were
collected during heating of previously cooled samples.

Complex dielectric response of a substance at frequency $\nu$ can be obtained
from specific capacitance $C(\nu)$ and conductivity $\sigma(\nu)$ using the
formula:

$\varepsilon(\nu)=\varepsilon^{\prime}-i\varepsilon^{\prime\prime}=\frac{C(\nu)}{\varepsilon_{0}}+\frac{\sigma(\nu)}{i2\pi\varepsilon_{0}\nu}$
(1)

Physical contribution to this response at low frequencies consists of several
inputs, including static ionic conductivity and intrinsic dielectric
permittivity of the sample with characteristic relaxation frequency $\nu_{0}$
and additional constant dielectric permittivity at “infinite” frequency. They
are usually described by the respective terms:

$\varepsilon(\nu)=i\frac{\sigma_{0}}{\nu}+\Delta\varepsilon\mathcal{R}(\nu/\nu_{0})+\varepsilon_{\infty}$
(2)

The contact polarization term Ishai  _et al._ (2013) is usually modeled with
constant phase element with impedance:

$Z_{p}\propto(i\nu)^{-n}$ (3)

(where $0<n<1$) connected in series with the sample. However, this
approximation should not be taken too seriously, because beside strong
deviation of dielectric permittivity from constant at low frequency region
(which is indeed observed in practice), it also results in unphysical decrease
of capacitance in high frequency region. So, one has to provide for a certain
cutoff function, able to describe faster fall off of dielectric responce at
higher frequencies (which is yet to be accomplished). Moreover, this approach
is usually applied to liquid samples, and it is not clear if it can describe
polarization of the sample in the solid form. This significantly undermines
separation of the terms, related to contact polarization, from intrinsic
sample relaxation and makes impossible direct fitting of experimental data
with the formula proposed. However, since intrinsic relaxation can be
described by purely Debye function in monoalcohols at low pressures Böhmer
_et al._ (2014):

$\mathcal{R}(\nu/\nu_{0})=\frac{1}{\left(1+i\nu/\nu_{0}\right)}$ (4)

it is possible to determine inflexion point on the dependence:

$\frac{1}{Z2\pi\nu}=\frac{1}{2\pi\nu(Z_{p}+1/(\varepsilon
2\pi\nu))}=\frac{\sigma_{eff}(\nu)}{2\pi\nu}+i\varepsilon_{eff}(\nu)$ (5)

which means that the response of sample and electrode polarization terms,
connected in series, is approximated by effective leaky capacitor with
frequency dependent conductivity $\sigma_{eff}$ and dielectric function
$\varepsilon_{eff}$ . This inflexion point marks transition from diverging
region, induced by electrode polarization effects at very low frequencies, to
constant term at somewhat higher frequencies, caused by the sample dielectric
relaxation and conductivity. Typical dielectric response, obtained by Equation
(5) is depicted in Fig. 2.

Figure 2: Effective dielectric function, caused by polarization effects.
Downward and upward arrows mark inflexion points due to the onset of
deviations, caused by electrode polarization effects in low frequency and
high-frequency region respectively. The sample was modeled, as element with
constant conductivity and capacitance (equal to 1). Polarization impedance was
approximated as constant phase element with exponent 0.7. Dashed horizontal
line marks position of “apparent” static dielectric constant of the sample (it
is slightly less than the true one).

Although it is very interesting to separate the frequency input of bulk solid
sample from polarization effects, it is well beyond the scope of present
paper. Still, gradual application of temperature with simultaneous collection
of dielectric permittivity data, applied in our experiments, helped us to
successfully separate these two inputs in premelting temperatures range. This
topic will be thoroughly discussed later on in Section IV. However, we should
stress once more, that our “continuous heating” approach is very different
from previous works on methanol and ethanol, where frequency scans at fixed
temperature were used.

##  III Dielectric spectroscopy of methanol

Figure 3: Dielectric response of methanol at ambient pressure at specified
temperatures. Figure 4: Temperature dependence of ambient pressure dielectric
permittivity of methanol at various frequencies ($\circ$–100 Hz, $\square$– 1
KHz, $\lozenge$– 10 kHz, $\triangledown$ – 100 kHz, $\triangle$– 1 MHz). Note
the log scale of $y$-axis.

Dielectric relaxation of methanol at ambient pressure at scans with constant
rate along temperature and frequency is presented in Fig. 3 (the scans were
collected at heating of previously crystallized sample). Another presentation
of the same data, as slices at fixed frequencies, is shown in Fig. 4. The main
conclusion that can be drawn from these data is, that freezing of methanol (at
180 K) leads to significant drop of dielectric constant
($\varepsilon^{\prime}$). Still, in solid phase of methanol, dielectric
response is frequency dependent, so the notion of dielectric constant in this
case needs some clarification. Large increase of dielectric constant at
frequencies below 1 kHz is due to contact polarization and can be regarded as
parasitic effect. This effect is also temperature dependent, and the onset of
contact polarization frequency is increased to 10 kHz near the melting
temperature. Still the dispersion observed in the frequency range 10 kHz-2 MHz
can be considered as intrinsic and connected to relaxation of the solid,
orientationally disordered methanol ($\beta$-phase). The presence of
disordered beta phase in methanol persists till very high pressures (at least
up to 6 GPa Kondrin  _et al._ (2013)).

Frequency slices at 100kHz, 1 MHz (see Fig. 4) distinctly demonstrate
transition at 165 K from orientationally disordered $\beta$-phase to
orientationally ordered low-temperature $\alpha$-phase of methanol, which is
accompanied by the drop of high frequency $\varepsilon^{\prime}$ from 7.7 to
3.9. This is in $\approx$ 1.5 margin corresponds to the results of Denney and
Cole Denney and Cole (1955) ( they report dielectric response in the
disordered phase of methanol in the range 4-6 at 5 K below the melting
temperature and fast increase of dielectric permittivity at approaching the
melting temperature). Nonetheless, in the intermediate temperature region
corresponding to the $\beta$-phase, dispersion of dielectric response is
observed, which can not be attributed to contact polarization. It manifests
itself as distinct step on the frequency dependent response of
$\varepsilon^{\prime}$ (see Fig. 3). This step shifts to lower frequencies
with the decrease of temperature (Fig. 3). Extrapolating this frequency
dependent response to low frequency region, we would get static dielectric
permittivity, approximately equal to $\varepsilon_{S}=38.9$. Further lowering
of temperature results in transition to fully ordered phase, where amplitude
of low-frequency relaxation process drops to zero. It should be noted that the
similar behavior in methanol below the melting temperature was observed in the
work of Denney and Cole Denney and Cole (1955). They carried out experiments
in setup with significantly larger separation of electrodes ($\approx$ 1 mm
vs. 0.1 mm in our case) so in their setup influence of electrode polarization
effects should be lower and restricted to lower frequencies. Still, they
report observation of dielectric dispersion in the range below 105 Hz which
they attributed to the intrinsic dielectric response of the sample. They also
report significant deviation of the dielectric response depending of the
thermal history, which can be due to the anisotropic character of the solid
phase (which the authors of Ref. Denney and Cole (1955) seems to support) but
as well to electrode polarization in the solid phase.

Near the melting temperature the amplitude of this relaxation rapidly
increases (up to values $\varepsilon_{L}\approx 70.8$) which is also
accompanied by rapid increase of frequency of corresponding relaxation
process. Thus, relaxation process rapidly moves out of the experimental
frequency window and dielectric response of the liquid methanol is
characterized by constant, but very high dielectric permittivity caused by
fast free fluctuation of molecular dipoles Denney and Cole (1955); Davidson
(1957); Bertolini  _et al._ (1983). It is interesting to note, that the
amplitude of dielectric process is increased by the value approximately equal
to 2
$(\varepsilon_{L}-\varepsilon_{\infty})/(\varepsilon_{S}-\varepsilon_{\infty})=2.02$.
We argue, that this increase is connected to increased hindrance on the
molecules’ free rotation in liquid and the solid $\beta$-phase of methanol.

Figure 5: Dielectric relaxation in liquid (solid curves) and disordered solid
phase (dashed curves) of the model substance, having two types of relaxation
(low and high frequency ones), which represents dielectric response of
methanol in the liquid and plastic crystal solid phase.

In the following we will need some model of dielectric relaxation in
monoalcohols. It is known to consist of two processes –the larger effect
observed at low frequencies is Debye relaxation ( at ambient pressure
relaxation can be well approximated by the Debye relaxation law) and the
weaker, high frequency one , called structural or $\alpha$-relaxation. It is
interesting to note, that in more complex (in comparison to methanol)
monoalcohols, the frequency of this weak relaxation usually corresponds to
processes, which govern thermodynamic and structural properties observed at
e.g. vitrification of monoalcohols Böhmer  _et al._ (2014); Danilov  _et al._
(2017) . Thus, despite its weakness in thermodynamic response, it is more
important in description of molecular dynamics of monoalcohols. Although in
application to methanol, exact P-T evolution of the Debye- and
$\alpha$-relaxations is not well known (which is mostly due to the fact, that
methanol vitrifies only at high pressures Brugmans and Vos (1995); Kondrin
_et al._ (2013) where precise spectroscopic techniques are not possible), but
our findings suggest that, separation into these two process exists in
methanol too. It can be concluded also from the experimental data of Barthel
et al. and Fukusawa et al. Barthel  _et al._ (1990); Fukasawa  _et al._ (2005)
where at room temperature the separation between the Debye relaxation process
and the next in frequency (presumably $alpha$ one) reaches almost one decade
(3.09 Ghz and 22.4 Ghz respectively).

To make this model more tractable, we propose simplified picture, describing
dielectric relaxation in liquid and solid phases of methanol Fig. 5. Note,
that dielectric losse $\varepsilon^{\prime\prime}$ connected to dielectric
permittivity $\varepsilon^{\prime}$ through the Kramers-Kroning relations so
the absorption peaks in the experimentally inaccessible high-frequency regions
manifests itself in the low-frequency region as plateaus in the dielectric
permittivity values. The picture shown in Fig. 5 suggests, that the frequency
separation between Debye and structural relaxation increases during
solidification of methanol (the frequency of the Debye process significantly
drops in the solid phase), while amplitude of the Debye relaxation decreases
in comparison to liquid state. This is in contrast to water, where amplitude
of dielectric relaxation remains constant in the melting process, while
frequency of Debye relaxation is dropped by several orders of magnitude Johari
and Whalley (1981); Ellison (2007); Aragones  _et al._ (2011). We consider
this difference between water and methanol as a manifestation of different
types of disorder, present in orientationally disordered solid phases. While
in solid water (ordinary hexagonal ice), the molecule can jump between four
positions and so the dielectric constant has the same value as in liquid
phase, where molecular dipole can freely rotate, in $\beta$-phase of methanol
(on the other hand) molecular dipoles can take only two collinear positions,
so corresponding dielectric permittivity value decreases in comparison to
liquid state. The rise of orientational disorder during transformation of
$\beta$-methanol into fully orientationally ordered phase would lead to
suppression of both relaxations (low- and high frequency ones) and
subsequently to drop of dielectric permittivity to lower values, which is
indeed observed in our experiments.

This difference is obviously connected to presence of methyl group, serving as
an anchor, preventing from molecule rotation in solid phase. However,
substitution of methyl by ethyl group ( as in ethanol) leads to drastically
different behavior in the low and high pressures which will be discussed later
in Sections V,VI.

##  IV Separation of electrode polarization effects from the bulk dielectric
response in methanol at ambient pressure

We would like to diverge on the topic of separation of electrode polarization
effects from the response of the sample in the case of liquid and solid
methanol. As it follows from Eqs. (2-4) the overall impedance of the sample is
the sum of two inputs: the “bare” sample impedance and the impedance due to
the electrode polarization which can be only roughly approximated by constant
phase element. Here, we will demonstrate that the separation of these two
effects in the series of experiments obtained at the one sample under varying
external conditions (e.g. varying temperature) does not require laborious
multiparametric fitting and can be carried out by the determination of
position and the value of only one critical point.

As it follows from Equations (2,3,4) in the low-frequency region ( where the
input of this two contributions is approximately equal) the relaxation part
and constant current conductivity can be described as leaky capacitor with
frequency independent dielectric constant $\varepsilon$ and conductivity
$\sigma$. The impedance of such element is given by the formula:

$Z(\nu)=\frac{1/\varepsilon}{\sigma/\varepsilon+i2\pi\nu}=\frac{A}{B+i\omega}$
(6)

I maginary part of this formula has distinct peak-like shape. The peak maximum
is located at $\omega=B$ and its maximum reaches the value $\frac{A}{2B}$. It
turns out (as it will be demonstrated below) that the value of this maximum
(in the vicinity of the maximum) is significantly higher than the impedance
caused by electrode polarization effects given by the Eq. (3) by almost order
of magnitude. So, determination of the value and position of this maximum
would allow us to determine the static conductivity and the low-frequency
dielectric constant of the sample itself.

Figure 6: Frequency dispersion of the real part of experimental impedance
$1/(\varepsilon\omega)$ of methanol at ambient pressure near the melting
temperature and $\alpha-\beta$ phase transition. $\circ$– corresponds to the
dielectric response in the liquid phase, $\square$– in the solid $\beta$
phase, $\lozenge$ – in the solid $\alpha$ phase. The temperatures in K at
which these data were collected is shown near the respective dependencies.
Dashed thin curves demonstrate deconvolution of dielectric response in the
liquid phase of methanol into electrode polarization part ($Z_{p}$) and the
part due to the bulk of the sample $Z$. Solid thick line is the contribution
from both parts $Z_{p}+Z$. In the inset the temperature dependence of static
dielectric constant determined from the local maxima of frequency dependence
of impedance is shown. The symbols shape corresponds to the respective curves
in the main panel. The vertical dashed lines marks temperatures of phase
transitions in methanol determined in our experiments. Solid lines are just
guides to the eyes and the temperature trends they depict may be exaggerated.

The experimental dielectric response of methanol converted into impedance
values at several fixed temperatures in vicinity of the melting region and
$\alpha-\beta$ phase transition is depicted in the main panel of Fig. 6.
Aforementioned maximum on frequency dependency of impedance is evident in all
these curves. Moreover, in the high temperature limit (in the liquid state and
just below liquid-$\beta$ phase transition) it is possible to separate the
input to overall dielectric response from the sample itself and the electrode
polarization effects. In the liquid state this enables us to fully deconvolve
the dielectric response into these two inputs. This yields the exponent $n$ of
electrode polarization of methanol in the liquid state which has the value
$n=0.81$. Variation of temperature influences both electrode polarization and
the sample dielectric response but from position of local maximum we can
extract data on the temperature dependence of static dielectric constant near
the melting temperature. This data is depicted in inset in Fig. 6.

First of all, from this data it follows that the “naive” separation of
constant $\varepsilon$ pertinent to the sample’s bulk by simply ignoring
divergent tail pertinent to the electrode polarization effects really works
under condition that the dielectric constant of the sample is large enough
(like in the liquid and the solid disordered $\beta$-phase of methanol). Both
approaches yield approximately equal values of dielectric constant:
$\varepsilon\approx 70$ for liquid state and constant (independent of
temperature) $\varepsilon\approx 35$ in the disordered $\beta$-phase. However,
the application of this procedure to the ordered $\alpha$-phase produce rather
unexpected result. It turns out that the dielectric constant at $\alpha-\beta$
transition drops to rather large value $\approx 15$ but further diminishes at
the temperature lowering (and reaches the value of $\approx 7$). This suggests
that the dielectric constant in the fully ordered phase of methanol increases
when the temperature approaches the order-disorder phase transition in the
solid state. So, this means that some amount of dynamic disorder is present
even in the nominally fully ordered phase in the vicinity of phase transition
and temperature rising increase the amount of this disorder. The similar
behavior is observed in the low-pressure solid phase of ethanol in vicinity of
melting temperature which will be discussed in the next Section V.

##  V Dielectric spectroscopy of ethanol at low pressures

Ambient pressure solid phase of ethanol (marked as I in Fig. 2 b) can by no
means be considered as orientationally disordered. Beside crystallographic
evidence Jönsson (1976); Allan and Clark (1999); Allan  _et al._ (2001), it
does not by large margin satisfy Timmerman’s criterion (its fusion entropy is
equal to 31 J/K mole). Similar conclusions can be derived from dielectric
spectroscopy experiments at ambient pressure, where transition from
$\varepsilon^{\prime}$ values equal to 75 at the melting temperature to 4-5 in
the fully solidified samples Hassion and Cole (1955); Brand  _et al._ (2000);
Kondrin  _et al._ (2014). The last value of dielectric permittivity is
compatible with the notion of induced polarization of ethanol molecules with
fully arrested molecular motion.

Figure 7: Experimental dielectric relaxation in liquid and solid low-pressure
phases of ethanol at 0.5 GPa. Figure 8: Dielectric relaxation frequency vs.
inverse temperature in ethanol at 0.5 GPa. “No relaxation region” corresponds
to the temperature region, where solidification of supercooled ethanol takes
place, and no relaxation in either glassy/supercooled liquid (lower
temperatures) or solid phase (higher temperatures) is observed. Solid blue
line is an Arrhenius extrapolation of relaxation frequency observed in the
solid phase of ethanol to the lower temperatures. Figure 9: Temperature
dependence of ethanol dielectric permittivity in the low (P=0.5 GPa, red
curves) and high pressure (P=2.5 GPa, blue curves) phases. Various symbols
correspond to different frequencies ($\circ$–100 Hz, $\square$– 1 KHz,
$\lozenge$– 10 kHz, $\triangledown$ – 100 kHz, $\triangle$– 1 MHz). Dashed
vertical lines mark onset of melting temperature. Downward arrow marks
transition from the high-pressure ordered phase to high-pressure
orientationally disordered phase accompanied by the increase of dielectric
permittivity.

It is worth noticing, that our dielectric spectroscopy experiments suggest
presence of slight orientational disorder in the vicinity of the melting
temperature at ambient pressure (which resembles the onset of disorder in
fully ordered $\alpha$-phase of methanol while approaching $\alpha$-$\beta$
phase transition). Still the overall behavior of dielectric relaxation is
quite different from the methanol case int he premelting region and we can not
designate distinct temperature region, in which ethanol transforms into
disordered state. Since the ethanol easily vitrifies upon cooling at low
pressures, it is easy to register both Debye and $\alpha$-relaxation
processes, being in experimentally attainable frequency range. However, glassy
state of ethanol is unstable and crystallizes upon heating (the cold
crystallization). Upon heating near the premelting region the disordering of
ethanol crystal phase takes place, which manifests itself in gradual increase
of dielectric permittivity in the low frequency region. The example of such a
relaxation is shown in Fig. 7. This dielectric response in this temperature
region is also frequency dependent and its extrapolated characteristic
frequency slightly below the frequency of the Debye relaxation collected in
the glassy/supercooled liquid state (see Fig. 8, where the data observed at
elevated pressure $P=0.5$ GPa are presented). The characteristic frequency of
relaxation process in glassy and solid phases of ethanol is obtained by
simultaneous fitting of real and imaginary part of dielectric responce by
simply ignoring polarization effects according to Equation 2 with relaxation
part described by Equation 4. This quite matches the model proposed for
description of relaxation in methanol but with very small downshift of
characteristic frequency during solidification. Still we would stress once
more, that the amplitude of this relaxation process monotonously depends on
temperature and one can find no kinks on the temperature dependence of low-
frequency dielectric permittivity which could be ascribed to phase transitions
to disordered high-temperature phase (see Fig. 9). The amplitude of dielectric
response gradually increases with temperature, approaching the melting
transition.

However, with crossing the pressure where the phase transition into high-
pressure crystal phase takes place, the dielectric response of solid ethanol
drastically changes. We consider this change as the evidence, that high
pressure phase of ethanol near premelting region is in the state of hindered
orientational disorder similarly to $\beta$-phase of methanol. However the
similarity between these two phases require further investigation which will
be carried out in the next Section VI.

##  VI Dielectric spectroscopy of ethanol at high pressures

Drastic difference between the high pressure and low-pressure crystal phases
of ethanol (obviously beside their different crystal structures Allan  _et
al._ (2001)) is that by cooling from the liquid we can not obtain glassy state
in the pressure region of high pressure phase stability (above 2.1 GPa)
Kondrin  _et al._ (2014). Stability region of high pressure phase of ethanol
is marked as II in Fig. 2 b). However, we will demonstrate, that beside that,
there is also difference in dielectric response of high pressure crystal
phase, which is not observed in the low pressure phase but makes the former
similar to disordered methanol phase.

Figure 10: Experimental dielectric relaxation in the liquid and solid high
pressure phases of ethanol at 2.5 GPa.

In Fig. 10 typical example of dielectric response collected at pressure
$P=2.5$ GPa is shown. In solid phase on the panel corresponding to real part
of dielectric response the distinct step-like feature is evident. Amplitude of
this feature is independent of temperature (while its characteristic frequency
is increased with temperature rise). We can evaluate relative amplitude of
this feature in respect to dielectric response of liquid ethanol as
$(\varepsilon_{L}-\varepsilon_{\infty})/(\varepsilon_{S}-\varepsilon_{\infty})=(48.9-7.4)/(31.6-7.4)=1.7$.
Still we observe, that the ratio is close to 2 (as in methanol) but
substantially lower. In our opinion, this discrepancy can be connected to the
significant hindrance of ethanol rotation in liquid phase, where longer
hydrogen bonded threads might be present. There is also a quite different
behavior of dielectric permittivity at fixed frequencies in comparison to the
data, collected at low pressures (see Fig. 9 ). At these high-pressure slices
a quite distinct kink (marked with arrow) is observed. which demarcates
premelting region of high dielectric permittivity from low temperature range,
where low values of dielectric constant are observed. So in the premelting
region, (which spans $T=288-335$ K range) dielectric response of solid ethanol
resembles that of $\beta$-phase of solid methanol with constant (independent
on temperature) value of static dielectric permittivity and high values of
high-frequency dielectric constant $\varepsilon_{\infty}$. It is possible that
these high-pressure phase of ethanol is similar to the orientationally
disordered metastable form of ethanol with $fcc$ structure which is produced
by special cooling treatment at ambient pressure Srinivasan  _et al._ (1996);
Ramos  _et al._ (1997); Jiménez-Ruiz  _et al._ (1999); Ramos  _et al._ (2007).
In this metastable phase it was also found that the dielectric relaxation
process is also diminishes by two times at temperature lowering during
transition to the orientational glass state Benkhof  _et al._ (1998); Jiménez-
Ruiz  _et al._ (1999). This might indicate that the orientational disorder in
this state also has hindered character.

We argue that the stability region of this partially orientationally high-
pressure disordered phase is higher in temperature than the stability region
of fully ordered phase II investigated by synchrotron radiation by Allan et
al. Allan  _et al._ (2001) at 2.75 GPa and room temperature. According to our
high-frequency dielectric spectroscopy data the transition to the fully
ordered phase takes place at temperatures 288 K at 2.5 GPa (marked by arrow in
Fig. 9) and 318 K at 3 GPa Kondrin  _et al._ (2014). So it is highly likely
that measurement of Allan et al. Allan  _et al._ (2001) were carried at
temperatures just below the transition into fully ordered phase of ethanol, so
the lowering of pressure below 2.5 GPa at room temperature (but above 2.1 GPa)
would result in transition into hindered plastic crystal phase of ethanol.

##  VII Discussion

So far we have demonstrated, that some sort of disorder present in crystal
phases of methanol and ethanol leads to significant increase of dielectric
constant. Moreover, it was found, that in oprientationally disordered phase of
methanol and high-pressure-high-temperature phase of ethanol it can lead to
the values of dielectric constant as high as several tens of $\varepsilon$.
The value of this constant practically does not depend on temperature, only
characteristic frequency of relaxational process giving rize for such a large
value of dielectric permittivity decreases with lowering the temperature.
However, common feature of all these phases is that the dielectric constant
being approximately two times less than that of liquid in the premelting
temperature region. We consider this an indication of hindered molecule
rotation in orientationally disordered phases in comparison to liquid phase,
and of the fact that in disordered crystal phase molecule’s rotation is not
free. We proposed to call such phases as hindered plastic crystals.

Further lowering of temperature induces transition of these plastic crystal
phases into fully ordered ones. So, the temperature stability region of
hindered plastic crystal phases is not large and spans 10-20 K. In fully
ordered phases at temperatures far from order-disorder transition the
dielectric constant is small (below 10) which indicates full extinguishing of
relaxational process of molecules as a whole and is likely to be caused by
induced polarization only. Beside low temperature phases of hindered plastic
crystal the low pressure phase of ethanol is also fully ordered one. However,
near the order-disorder transition we observe the increase of dielectric
constant, which indicates thawing of rotational molecular degrees of freedom.
So, fully ordered phases of lower-weight monoalcohols differ from hindered
plastic crystal phases not only in characteristic frequency of relaxational
process, giving rize to large dielectric constant depends on temperature but
its amplitude too.

It is interesting to compare dielectric response of hindered plastic crystals
of ethanol and methanol to that of classical example of plastic crystal
monoalcohol – cyclooctanol (with entropy of fusion as low as 6.98
$J/(K~{}mole)$ Ściesiński  _et al._ (1995)). Its dielectric properties were
investigated in number of works (see e. g. the works Brand  _et al._ (1997);
Michl  _et al._ (2015); Drozd-Rzoska  _et al._ (2021, 2022)). In contrast to
high-pressure phase of ethanol and $\beta$-phase of methanol , dielectric
constant of cyclooctanol does not decrease, but slightly increases during
freezing of liquid phase Drozd-Rzoska  _et al._ (2021). This is accompanied
with slight decrease (less than one order) of characteristic frequency of
relaxational process Drozd-Rzoska  _et al._ (2022). So, this indicates that in
contrast to methanol and ethanol, rotation of cyclooctanol molecule in plastic
crystal phase is practically free. In this respect it resembles ordinary
hexagonal ice. However, in our opinion, the cause of absence of hinderance of
molecular rotations in cyclooctanol is different and may be due to the
presence of large molecular “tail” of cyclooctanol. Interaction of these tails
prevents formation of more tightly bound hydrogen-bonded chains in plastic
crystal phase of cyclooctanol. So, in crystal phase of cyclooctanol there is
no definite direction, along which the hydrogen bonds can align.

There is another similarity between water and cyclooctanol in regard of their
transition into fully ordred phase. Hexagonal ice is notorious for difficulty
of proton ordering at low temperatures, and it usually requires addition of
external components (like ionic salt LiCl) to facilitate it. Similar situation
is true for cyclooctanol, where orientational disorder tends to “vitrify” in
process of lowering the temperature . It is definetely opposite to ethanol and
methanol, where hindered plastic crystal phases exist in very limited
temperature range. How it can be connected with the hindrance of molecular
rotation, is the question yet to be resolved.

##  VIII Conclusions and final remarks

Our first main conclusion is that static dielectric permittivity of methanol
in orientationally disordered $\beta$-phase is significantly higher than
supposed before. Our measurements in the premelting region suggest, that in
disordered solid phase of methanol, relaxational process typical to
reorientation motion of molecules still exists, but significantly shifts to
the low frequency region. Due to the hindered motion of molecules in this
solid phase in comparison to almost free motion in liquid phase, the amplitude
of dielectric relaxation in solid $\beta$-phase of ethanol is almost twice
lower, than relaxation amplitude in liquid phase near melting temperature.
This is different from ordinary ambient-pressure water, where dielectric
relaxation shift to the low-frequency region upon crystallization is not
accompanied with lowering of amplitude of this relaxation. This enables us to
distinguish between true plastic crystals (like ice), where rotation of the
molecules’ dipole moment is free in crystal phase and hindered plastic crystal
(like methanol), where rotation of dipole moment is restricted to certain
plane. In methanol, the axis normal to this plane is the line, connecting
carbon and oxygen atoms.

We argue, that the phase similar to hindered plastic crystal phase of methanol
exists at high pressures in another small-molecule monoalcohol - ethanol too.
Low pressure phase of ethanol is obviously ordered, but application of high
pressure (above 2.1 GPa) and temperatures leads to orientational disordering
of its molecules. We have found, that amplitude ratio of relaxational process
observed in solid high-pressure high-temperature phase of ethanol relative to
one observed in liquid phase is close to two, but substantially lower
(approximately equal to 1.7). We believe, that the decrease of this
coefficient indicates somehow hindered motion of ethanol molecules in high-
pressure liquid phase, compared to methanol.

We should also mention that these results were only possible due to our
experimental setup which allows us to collect dielectric responce during
simultaneous heating and scanning the frequency. Also there was significant
breakthrough in data processing procedure that enables us to separate
electrode polarization effects from the dielectric relaxation of the sample in
the low frequency region and unambiguously establish the value of static
dielectric constants in the solid phases of ethanol and methanol.

## References

  * Timmermans (1961) J. Timmermans, Journal of Physics and Chemistry of Solids 18, 1 (1961).
  * Kondrin  _et al._ (2013) M. V. Kondrin, A. A. Pronin, Y. B. Lebed, and V. V. Brazhkin, The Journal of Chemical Physics 139, 084510 (2013).
  * Kondrin  _et al._ (2014) M. V. Kondrin, A. A. Pronin, and V. V. Brazhkin, The Journal of Chemical Physics 141, 194504 (2014).
  * Onsager and Runnels (1969) L. Onsager and L. K. Runnels, The Journal of Chemical Physics 50, 1089 (1969).
  * Ryzhkin  _et al._ (2020) M. I. Ryzhkin, I. A. Ryzhkin, A. M. Kashin, and V. V. Sinitsyn, JETP Letters 112, 498 (2020).
  * Tauer and Lipscomb (1952) K. J. Tauer and W. N. Lipscomb, Acta Crystallographica 5, 606 (1952).
  * Allan  _et al._ (1998) D. R. Allan, S. J. Clark, M. J. P. Brugmans, G. J. Ackland, and W. L. Vos, Phys. Rev. B 58, R11809 (1998).
  * Torrie  _et al._ (1989) B. Torrie, S.-X. Weng, and B. Powell, Molecular Physics 67, 575 (1989).
  * Torrie  _et al._ (2002) B. Torrie, O. Binbrek, M. Strauss, and I. Swainson, Journal of Solid State Chemistry 166, 415 (2002).
  * Gainaru  _et al._ (2010) C. Gainaru, R. Meier, S. Schildmann, C. Lederle, W. Hiller, E. A. Rössler, and R. Böhmer, Phys. Rev. Lett. 105, 258303 (2010).
  * Böhmer  _et al._ (2014) R. Böhmer, C. Gainaru, and R. Richert, Physics Reports 545, 125 (2014).
  * Gonzalez-Salgado and Vega (2016) D. Gonzalez-Salgado and C. Vega, The Journal of Chemical Physics 145, 034508 (2016).
  * Červinka and Beran (2018) C. Červinka and G. J. O. Beran, Chem. Sci. 9, 4622 (2018).
  * Ellison (2007) W. J. Ellison, Journal of Physical and Chemical Reference Data 36, 1 (2007).
  * Johari and Whalley (1981) G. P. Johari and E. Whalley, The Journal of Chemical Physics 75, 1333 (1981).
  * Denney and Cole (1955) D. J. Denney and R. H. Cole, The Journal of Chemical Physics 23, 1767 (1955).
  * Davidson (1957) D. W. Davidson, Canadian Journal of Chemistry 35, 458 (1957).
  * Khvostantsev  _et al._ (2004) L. G. Khvostantsev, V. N. Slesarev, and V. V. Brazhkin, High Pressure Research: An International Journal 24, 371 (2004).
  * Pronin  _et al._ (2010a) A. A. Pronin, M. V. Kondrin, A. G. Lyapin, V. V. Brazhkin, A. A. Volkov, P. Lunkenheimer, and A. Loidl, Phys. Rev. E 81, 041503 (2010a).
  * Pronin  _et al._ (2010b) A. A. Pronin, M. V. Kondrin, A. G. Lyapin, V. V. Brazhkin, A. A. Volkov, P. Lunkenheimer, and A. Loidl, JETP Letters 92, 479 (2010b).
  * Kondrin  _et al._ (2012) M. V. Kondrin, E. L. Gromnitskaya, A. A. Pronin, A. G. Lyapin, V. V. Brazhkin, and A. A. Volkov, The Journal of Chemical Physics 137, 084502 (2012).
  * qua (1997) _7600 Precision LCR Meter Model B Instruction Manual_ (1997).
  * Ishai  _et al._ (2013) P. B. Ishai, M. S. Talary, A. Caduff, E. Levy, and Y. Feldman, Measurement Science and Technology 24, 102001 (2013).
  * Bertolini  _et al._ (1983) D. Bertolini, M. Cassettari, and G. Salvetti, The Journal of Chemical Physics 78, 365 (1983).
  * Danilov  _et al._ (2017) I. Danilov, A. Pronin, E. Gromnitskaya, M. Kondrin, A. Lyapin, and V. Brazhkin, The Journal of Physical Chemistry B 121, 8203 (2017).
  * Brugmans and Vos (1995) M. Brugmans and W. Vos, The Journal of Chemical Physics 103, 2661 (1995).
  * Barthel  _et al._ (1990) J. Barthel, K. Bachhuber, R. Buchner, and H. Hetzenauer, Chemical Physics Letters 165, 369 (1990).
  * Fukasawa  _et al._ (2005) T. Fukasawa, T. Sato, J. Watanabe, Y. Hama, W. Kunz, and R. Buchner, Phys. Rev. Lett. 95, 197802 (2005).
  * Aragones  _et al._ (2011) J. L. Aragones, L. G. MacDowell, and C. Vega, The Journal of Physical Chemistry A 115, 5745 (2011).
  * Jönsson (1976) P. G. Jönsson, Acta Crystallographica Section B 32, 232 (1976).
  * Allan and Clark (1999) D. R. Allan and S. J. Clark, Phys. Rev. B 60, 6328 (1999).
  * Allan  _et al._ (2001) D. R. Allan, S. Parsons, and S. J. Teat, Journal of Synchrotron Radiation 8, 10 (2001).
  * Hassion and Cole (1955) F. X. Hassion and R. H. Cole, The Journal of Chemical Physics 23, 1756 (1955).
  * Brand  _et al._ (2000) R. Brand, P. Lunkenheimer, U. Schneider, and A. Loidl, Phys. Rev. B 62, 8878 (2000).
  * Srinivasan  _et al._ (1996) A. Srinivasan, F. J. Bermejo, A. de Andrès, J. Dawidowski, J. Zùñiga, and A. Criado, Phys. Rev. B 53, 8172 (1996).
  * Ramos  _et al._ (1997) M. A. Ramos, S. Vieira, F. J. Bermejo, J. Dawidowski, H. E. Fischer, H. Schober, M. A. Gonzàlez, C. K. Loong, and D. L. Price, Phys. Rev. Lett. 78, 82 (1997).
  * Jiménez-Ruiz  _et al._ (1999) M. Jiménez-Ruiz, M. A. González, F. J. Bermejo, M. A. Miller, N. O. Birge, I. Cendoya, and A. Alegría, Phys. Rev. B 59, 9155 (1999).
  * Ramos  _et al._ (2007) M. A. Ramos, V. Rodrìguez-Mora, and R. J. Jimènez-Riobòo, Journal of Physics: Condensed Matter 19, 205135 (2007).
  * Benkhof  _et al._ (1998) S. Benkhof, A. Kudlik, T. Blochowicz, and E. Rössler, Journal of Physics: Condensed Matter 10, 8155 (1998).
  * Ściesiński  _et al._ (1995) J. Ściesiński, J. Mayer, T. Wasiutyński, E. Ściesińska, and J. Wójtowicz, Phase Transitions 54, 15 (1995).
  * Brand  _et al._ (1997) R. Brand, P. Lunkenheimer, and A. Loidl, Phys. Rev. B 56, R5713 (1997).
  * Michl  _et al._ (2015) M. Michl, T. Bauer, P. Lunkenheimer, and A. Loidl, Phys. Rev. Lett. 114, 067601 (2015).
  * Drozd-Rzoska  _et al._ (2021) A. Drozd-Rzoska, S. Starzonek, S. J. Rzoska, J. Łoś, Z. Kutnjak, and S. Kralj, Molecules 26, 429 (2021).
  * Drozd-Rzoska  _et al._ (2022) A. Drozd-Rzoska, S. J. Rzoska, A. Szpakiewicz-Szatan, S. Starzonek, J. Łoś, and K. Orzechowski, Journal of Molecular Liquids 345, 117849 (2022).


# Provenance for Linguistic Corpora Through Nanopublications

Timo Lek1, Anna de Groot1, Tobias Kuhn1, Roser Morante2
1Department of Computer Science, Faculty of Science, Business Web and Media
2CLTL Lab, Faculty of Humanities
Network Institute, VU Amsterdam
<EMAIL_ADDRESS><EMAIL_ADDRESS>
###### Abstract

Research in Computational Linguistics is dependent on text corpora for
training and testing new tools and methodologies. While there exists a
plethora of annotated linguistic information, these corpora are often not
interoperable without significant manual work. Moreover, these annotations
might have evolved into different versions, making it challenging for
researchers to know the data’s provenance. This paper addresses this issue
with a case study on event annotated corpora and by creating a new, more
interoperable representation of this data in the form of nanopublications. We
demonstrate how linguistic annotations from separate corpora can be reliably
linked from the start, and thereby be accessed and queried as if they were a
single dataset. We describe how such nanopublications can be created and
demonstrate how SPARQL queries can be performed to extract interesting content
from the new representations. The queries show that information of multiple
corpora can be retrieved more easily and effectively because the information
of different corpora is represented in a uniform data format.

##  1 Introduction

The availability of annotated linguistic corpora is crucial to develop Natural
Language Processing (NLP) systems [Chiarcos, 2012, Van Son et al., 2018]. In
the past couple of decades, many linguistic resources have been released,
which contain different types of annotations, from morphosyntactic to semantic
and discourse level annotations. However, they often lack structural and
conceptual interoperability [Chiarcos, 2012]. The former is related to the
data format of annotations, such as XML-standoff or RDF representations, while
the latter refers to the possibility of exchanging information in a consistent
and mappable way. Diverging annotation guidelines, the structure of annotated
output, and the different amounts of annotations created per corpus pose a
challenge in organizing the provenance of corpora.

Often, annotation projects run on (subsets of) existing text corpora, which
are thereby annotated with multiple annotation layers. Unfortunately, the
format for linking annotations to the texts is mostly not standardized and
these links therefore are often not fully precise or directly interoperable.
This makes it challenging for a researcher to figure out the data’s exact
provenance and to integrate annotations from several corpora. Integrating
different annotations is valuable because it can help scholars study and
understand the different interdependencies between annotation layers (e.g.
semantic parsers usually take syntactic structure in consideration).

Moreover, often the annotations follow idiosyncratic guidelines that pursue a
specific annotation goal. The need to organize the various existing
annotations has been recognized by the corpus linguistic community [Chiarcos,
2012, Kilgarriff, 2001]. While a number of solutions to improve linguistic
Linked Data have been presented in the past, we propose here a novel approach
that uses the Linked Data format of nanopublications to represent annotated
corpora in a more fine-grained semantic format, with the aim of boosting the
interoperability of linguistic corpora and facilitating the automatic
integration of annotations in a reliable and transparent manner.

Our research is motivated by the empirical analysis on 20 event-annotated
corpora presented in [Van Son et al., 2018], which highlighted the challenges,
as well as the opportunity, of event corpora interoperability. Existing event
annotation standards range from annotations about the participants,
timing/temporal order, factuality, and entity coreference relation, making a
standardized description of an event difficult. This is where nanopublications
as a fine-grained and provenance-aware data format could provide transparency
and interoperability for computational linguistic research.

For our case study, we have chosen to focus on integrating annotations from
two corpora, FactBank [Saurí and Pustejovsky, 2009] and PARC 3.0 [Pareti,
2016]. In PARC, attribution relations and their components (Cue, Content,
Source) are annotated, while in FactBank events and their factuality values
(i.e. the certainty of the occurrence of an event) are annotated. It is
interesting to combine the two annotation layers in order to extract, for
example, which events occur in the content of attribution relations and what
are their factuality values. Figure 1 presents the same sentence annotated in
PARC and FactBank.

Figure 1: An example sentence with its annotations in FactBank and PARC.

Our main contributions thereby are (1) providing a fine-grained and
interoperable Linked Data representation of annotated linguistic corpora in
the form of nanopublications, (2) analysing the main interoperability problems
that we encountered and solved with our nanopublication-based approach, and
(3) demonstrating how the concrete annotations from our case study of two
corpora can be integrated with nanopublications and queried with SPARQL.

We describe below how we converted these corpora into nanopublications and
then report on the interoperability challenges faced and solved with our
approach by representing the data in a uniform manner using nanopublications.
Finally, we discuss based on our results the extent to which nanopublications
can be seen as a viable alternative for improved linguistic corpora
interoperability.

##  2 Linked Data, Data Provenance and Nanopublications

Linked Data is about connecting and publishing data in a structured way on the
web, often on the basis of an ontology using the Web Ontology Language (OWL)
[McGuinness et al., 2004]. The data is often structured in triples using the
Resource Description Framework (RDF). By using unique URIs for each entity of
information, these entities can be interlinked in order to create an entire
web of data [Bizer et al., 2011].

Several projects were already performed to create linked linguistic data.
Since 2012, six series of Linked Data in Linguistics (LDL) workshops have been
hosted to gather and discuss contributions promoting linking linguistic data.
After the second workshop, one of the presented efforts was the Linked
Linguistic Open Data (LLOD) cloud.111https://linguistic-lod.org/While creating
the LLOD cloud, a lot of linguistic data was already available, which were
mostly represented using RDF. One example is WordNet, which is also part of
the Semantic Web [Gangemi et al., 2003, Chiarcos et al., 2013]. Furthermore,
Chiarcos proposed to represent linguistic corpora into OWL and RDF to
interlink all of the different resources of corpora. In this way, the
annotations of the corpora could be linked using terminological resources like
standardized annotation formats [Chiarcos, 2012].

Existing approaches that aim to represent the structure and content of natural
language and its annotations include the Ontology Lexicalisation and the
Ontologies of Linguistic Annotation (OLiA) [Villegas and Bel, 2015, Buitelaar
et al., 2011, Bosque-Gil et al., 2015]. OLiA focuses on annotations of
linguistic corpora and can be seen as a source that references to the
‘annotation terminology’ that can be used in combination with the LLOD to
capture all of the information of the annotations in the LLOD in a similar
format [Chiarcos and Sukhareva, 2015].

Since all different texts and annotations in a corpus may have a different
origin, i.e. provenance, provenance ontology PROV222https://www.w3.org/ns/prov
can be used for this. This ontology contains different classes and properties
that represent the provenance information in different contexts, thereby
usable for keeping track of the provenance information of linguistic corpora.
The PROV ontology has been shown to be applicable to a diversity of fields to
track provenance information in a general manner [Lebo et al., 2013].

Even though the RDF language is not optimized for this, the NLP Interchange
Format (NIF)333http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core
makes it possible to represent texts and their elements in RDF, primarily by
using strings. With the NIF ontology, a context, sentence, phrase, or word can
be represented into RDF triples. It is also possible to have references
between different levels, so a word can reference to another part of the RDF
scheme that is the sentence from where it was derived. In a study by Menke et
al. it was suggested to improve the reprensentation of the provenance
information of the annotations in the NIF ontology by introducing a new
ontology called MOND, which uses the PROV ontology to include provenance
information in the NIF ontology [Menke et al., 2017].

Moreover, many annotation guidelines exist and each is usually represented in
a different structure, increasing the difficulty in creating a standard model
to transform annotations into RDF. The Web Annotation Vocabulary [Sanderson et
al., 2017], for example, provides a possible solution with relations such as
‘motivatedBy’ and ‘hasTarget’, making it possible to structure annotations in
an interoperable way.

Nanopublications are a format for small data publications based on RDF
triples, consisting of three parts: the assertion, provenance, and publication
information [Kuhn et al., 2013]. The assertion contains the main content of a
nanopublication, for example stating in a formal way the link between a gene
and a disease. The provenance part states how this assertion came to be, by
linking to the study that was performed or the paper from which the assertion
was extracted. The publication information part, finally, records information
about the nanopublication itself, such as by who and when it was created
[Groth et al., 2010]. In a previous work, a Java library for nanopublications
was created, which can also be used as a command line tool [Kuhn, 2015].
Nanopublications can be given _trusty URIs_ as identifiers, which include a
hash value of the complete content, and thereby make nanopublications
immutable and verifiable [Kuhn and Dumontier, 2014]. Such nanopublications can
then be reliably and redundantly published to the existing distributed server
network [Kuhn et al., 2016]. Each of these servers contains all
nanopublications, making it possible to retrieve the nanopublication from
another server when one server is down. Nanopublications also allow for
precise and reliable versioning, as well as the definition of incremental
datasets by defining nanopublication indexes [Kuhn et al., 2017]. Such indexes
are represented as nanopublications themselves that contain links to other
nanopublications and thereby defining sets of nanopublications.

##  3 Methodology

In this section we introduce our methodology to address the above-mentioned
problems of interoperability and provenance of text corpora by applying the
concept and techniques of nanopublications. To demonstrate and evaluate this
methodology, we then present a case study. We introduce a number of questions
on the combined annotations that can be answered in an integrated and
automatic manner through SPARQL queries. Through the SPARQL queries we will
show that data of multiple corpora can be retrieved using a single query,
solving the interoperability issues.

###  3.1 Nanopublication Model for Text Corpora

Figure 2: General nanopublication scheme with examples.

In Figure 2, we present a general scheme for representing text corpora and
their annotations as a network of interconnected nanopublications. This model
ensures that new information from other corpora could easily be linked to
existing nanopublications, through the addition of more nodes to the network.
The nanopublications that form this general structure can be divided into four
groups depending on what they represent: text, annotation, corpus, and index
nanopublications.

First, at the top of the figure the text-corpus nanopublication can be found.
This nanopublication contains the information regarding the text corpus, which
is the set of original texts. It is linked to an index nanopublication which
points to all document, text, and word nanopublications which are part of the
corpus. The document and text nanopublications can be part of multiple corpora
and thus multiple index nanopublications. These document nanopublications
contain all of the metadata on the actual texts, namely the provenance
information, title, and identifier. Furthermore, the document nanopublications
have a link to the nanopublication containing the actual text corresponding to
the metadata. Both the document and the text nanopublication also contain a
back-reference to their corpus nanopublication.

Additionally, word nanopublications are created, as words are the typical
targets of annotations. They contain the word string, sentence number, and the
offset values with respect to the text, and possibly other word-level
information (e.g. their part-of-speech value). Thereby, each word gets its own
URI as identifier, which is constructed from the text URI and the word’s
offset values. From the bottom, annotation corpora are pointing to these
words. Similar to the text corpora, a corpus nanopublication of an annotation
corpus contains the general corpus-level information, most importantly a link
to an index nanopublication pointing to all annotation nanopublications. Their
concrete content depends on the type of annotation, but they all point to the
words they are annotating via the URIs as described above. For convenience,
they are also pointing back to the overall annotation corpus nanopublication.

Modeling these elements as small self-contained entities has also the
advantage that differences in licenses can be defined and handled on a fine-
grained level. Often, annotations have a different, sometimes more permissive,
license than the texts they annotate. For this, we introduce the
nanopublication type ProtectedNanopub that we use to mark nanopublications
that cannot be openly published due to license reasons. We updated the
nanopublication client and server code such that an error is raised if a user
accidentially tries to publish such a protected nanopublication to the server
network.

Lastly and importantly, our approach is open for anybody to publish further
annotations or texts as nanopublications. These wouldn’t be directly included
in the datasets, as the index nanopublications don’t point to them, but they
can be found by querying the nanopublication network, and included if desired
in a given situation. Moreover, a new version of a corpus can include such
“third-party” contributions, thereby making them a proper part but also
clearly attributing the third-party contributor, which is defined in the
provenance and publication info parts. This also allows for corrections to be
published by anybody who finds something that is wrong.

###  3.2 Case Study Design

The case study workflow has 3 main components: (1) obtain and analyze original
and annotated corpora; (2) convert these into nanopublications; and (3) assess
the usefulness of the nanopublication representations. We evaluate on two
event-related linguistic corpora, FactBank and PARC 3.0. For PARC, we process
34 annotation files that provide annotations on Wall Street Journal Corpus
(WSJ) documents. For FactBank, we process 194 documents, which provide
annotations on WSJ, New York Times (NYT), Associated Press Writer (APW)
documents, and documents from several other sources. Thus, we use the
intersection of 34 WSJ documents for which both corpora provide annotations
for investigating the extent to which nanopublications indeed facilitate
automated merging and interoperability.

The PARC corpus provides annotations about attribution relations, which are
made up of three components a Source, a Content, and a Cue. The original
annotations are made at the token-level and are presented in XML format. The
FactBank corpus includes annotations about events and their factuality values.
FactBank adopts event annotations from the TimeML annotations [Saurí et al.,
2006], while it defines event factuality with a value that represents how
certain or true an event is according to a source present in the text.
FactBank has six primary factuality values present in its annotations. These
annotations are contained in a set of 20 tables, each written in a separate
text file. We refer the reader to [Saurı, 2008] and [Pareti, 2015] for
detailed explanations of each annotation scheme, and we will elaborate below
on their interoperability challenges.

For this case study, we came up with six general questions that somebody who
would like to use the above annotations might want to ask. These questions are
shown in Table 1. One of our goals is answering questions that show the
merging capabilities and efficiency of nanopublications. For example, the
answer to Q3, depending on the factuality values it outputs, might suggest how
certain the content of the text is. An answer to Q6 might help an annotator
clarify doubts during the annotation process, and Q5 demonstrates how FactBank
events can be related to PARC attribution relations. Some questions ask only
for information from one corpus, while others are more complex by requiring
information from both corpora. We will use these general questions to make
them automatically executable with our integrated nanopublication model and
the SPARQL query language.

|  Question
---|---
Q1 |  Who talked about an event, and what is the factuality value of that event?
Q2 |  Which events have multiple factuality value annotations?
Q3 |  What are the different factuality values expressed per document, and which values appear the most?
Q4 |  How often are certain annotation values used? (e.g. the count of different factuality values represented or the count of different sources)
Q5 |  How many of the annotated FactBank events are labelled with a specific attribution component?
Q6 |  Where in the corpus is a specific word (or lemma) assigned a specific attribution label (e.g. where is the verb ‘to surprise’ annotated as Cue?
Table 1: Case study questions.

##  4 Case Study

We applied the nanopublication-based approach to the case study in order to
address the problem of interoperability and provenance. Different types of
nanopublications were created to represent the chosen corpora. As introduced
above, nanopublications consists of an assertion, provenance, and publication
info part. In these nanopublications the publication info part is similar for
all our nanopublications, containing the date of creation, license, ORCID
identifiers of the creators, and sometimes further comments and website links.
All the text and word nanopublications, as well as the annotations of
FactBank, are also marked as protected, due to their private licences. The
remaining nanopublications are public and can therefore be published to the
server network for public accessibility. The dataset of all public
nanopublications can be found online.444https://github.com/ucds-vu/provcorp-
model

We defined four corpus nanopublications for our case study: one for the text
contained in the corpus and one for the annotations contained in the corpus,
for each of the two existing corpora (PARC and FactBank). They contain basic
information about the corpus and link to their content via an index
nanopublication, as can be seen in this example (abbreviated here and below
for readability):

⬇

sub:assertion {

corpus:parc-annotations a pvcp:AnnotationCorpus;

dct:title "PARC Annotation corpus";

rdfs:seeAlso <https://www.aclweb.org/anthology/L16-1619.pdf>;

dcat:distribution indexnp: .

}

Via their index nanopublications, they point to 194 document nanopublications,
which contain the document metadata. This is an example:

⬇

sub:assertion {

sub:document a foaf:Document;

dct:title "Financing Business: @ Rogers Communications Inc.";

dct:created "1989-11-02T00:00:00"^^xsd:dateTime;

dct:creator <http://dbpedia.org/resource/The_Wall_Street_Journal>;

pvcp:hasText textnp:text .

}

These document nanopublications link to the actual text using pvcp:hasText to
point to the text nanopublication. An example of the latter is shown here:

⬇

sub:assertion {

sub:text a nif:OffsetBasedString, dct:Text;

rdf:value """ ROGERS COMMUNICATIONS Inc. said it plans to raise 175 million to
180 million Canadian dollars (US$148.9 million to $153.3 million) through a
private placement of perpetual preferred shares. ... He declined to discuss
other terms of the issue. """ .

}

The word nanopublications point back to the text nanopublication and provide
word-level information including the word string, the offset of this string
with respect to the text, and the sentence number. They can also contain lemma
and part-of-speech information. As this word level depends on tokenization,
there can be differences in how different annotation corpora define word
boundaries. For this reason, our approach allows for the generation of new
word nanopublications on demand. This creates an identifier for the word based
on the URI of the text nanopublication and the offset of the word, thereby
assuring that words introduced several times by different annotation corpora
get the same identifier and are therefore immediately interoperable. In our
case, we have 6,362 word nanopublications defined from PARC and 7,784 from
FactBank. This is an example of the former:

⬇

sub:assertion {

textoffset:3-9 a nif:OffsetBasedString, nif:Word;

nif:beginIndex "3"^^xsd:int;

nif:endIndex "9"^^xsd:int;

nif:anchorOf "ROGERS";

nif:lemma "rogers";

olia:POS "NNP";

pvcp:hasSentenceNumber "0"^^xsd:int;

pvcp:isPartOfText textnp:text .

}

The annotations can now link to these words. We have 136 annotation
nanopublications for PARC, that associate words with content, cue and source
annotations, as can be seen in the example below:

⬇

sub:assertion {

sub:annotation a oa:Annotation;

dct:isPartOf corpus:parc-annotations;

pvcpp:hasContentAnnotatedWord textoffset:101-106, textoffset:107-114, ...;

pvcpp:hasCueAnnotatedWord textoffset:30-34;

pvcpp:hasSourceAnnotatedWord textoffset:10-24, textoffset:25-29,
textoffset:3-9 .

}

For FactBank, we have annotation nanopublications that declare events (7,784)
and separate ones annotating their factuality values (10,948), with a similar
structure as the PARC nanopublications above.555The complete set of
nanopublications can be found here: https://github.com/ucds-vu/provcorp-model

We have focused above only on the assertion part, but all these
nanopublications also come with specific provenance and publication
information, for example describing that the PARC annotations were created at
a different time by a different person than the nanopublications themselves.

##  5 Results

In this section we analyze the interoperability challenges we faced and
addressed with our approach and assess the extent to which we can
automatically answer the questions we introduced above.

###  5.1 Analysis of Addressed Challenges

| Addressed Challenge | corpus | abs. | rel.
---|---|---|---|---
1. | Incompatible text offsets | PARC/FactBank | 194 | 100.0%
2. | Metadata included in sentence number count | FactBank | 194 | 100.0%
3. | Insufficient sentence splitting information | FactBank | 64 | 33.0%
4. | Missing headline | FactBank | 33 | 17.0%
5. | Inconsistent use of text tags | FactBank | 23 | 11.9%
6. | Absence of text tags to structure the document | FactBank | 17 | 8.8%
7. | Unknown journal / source | FactBank | 16 | 8.2%
8. | No attribution relations for the document | PARC | 4 | 2.0%
9. | Incompatible sentence splitting at semicolons | PARC/FactBank | 2 | 1.0%
10. | Annotations on the headline | FactBank | 1 | 0.5%
Table 2: Overview of addressed interoperability challenges, including their
absolute and relative frequencies in the 194 documents of our case study
corpora.

With our case study as described above, we encountered a number of
interoperability challenges. We managed to resolve almost all of them in our
manual conversion work as described above. However, we had to exclude ten
documents of FactBank due to the fact that sentence numbers were skipped when
a sentence ended with a double quote ("), and we did not have enough
information to correct this mistake. In Table 2, we show an overview of the
challenges we successfully addressed on the remaining 194 documents. This
highlights the nature and extent of interoperability problems that come with
the current way how such corpora are published but would be resolved if our
approach was followed, i.e. if they would be published as interoperable
nanopublications from the start.

The first issue on the list are text offsets. PARC and FactBank locate words
in a text differently: PARC uses byte counts, whereas FactBank makes use of
sentence and token numbers. Token numbers are tokenizer-specific, so
FactBank’s method is quite sensitive and difficult to replicate. FactBank’s
sentence numbers are moreover confusing as they also count the metadata
fields, such as text headings, and not just the text content (which is
challenge number 2). PARC, on the other hand, also has its quirks, such as
including the six characters of the initial <TEXT> tag in the offset count. In
our nanopublications, we use text offsets that unambiguously link to the text
string of the content, and thereby ensure precise and interoperable text
references.

For FactBank’s sentence and token number approach to refer to words in the
text, it is crucial to know where a sentence ends and a new one starts. This
sentence splitting, similar to tokenization mentioned above, is sensitive to
the used algorithm. This is why text corpora like WSJ provide us with this
sentence splitting information by saving each sentence on a separate line in
the provided file formats. However, the documents from NYT and APW didn’t have
this information and so these sentences had to be checked manually for the
correct splitting (challenge 3). Moreover, sentences containing a semicolon in
PARC are annotated as one sentence while they are considered two sentences in
FactBank (challenge 9).

Challenges 5 and 6 point to the fact that text tags were used inconsistently.
The main text is included in <TEXT> tags, but these were missing for 17
documents. Moreover, WSJ documents use <HL> and <DATELINE> tags for the
headline and date, respectively, while NYT and APW documents use <HEADLINE>
and <DATE_TIME>. Some documents moreover, did not contain tags at all, and we
had to add them manually.

Normally, headlines are not annotated, but there is an exception in document
APW19980213.1380, which includes an annotation of a part of the headline
(challenge 10). Upon encountering this situation, we extended our model to
also allow for headline annotations. Lastly, in some cases metadata was
missing. Some documents did not have a headline (challenge 4) or did not
include a journal or source (challenge 7). In PARC, there were also four
documents that did not contain any attribution relations (challenge 8).

In summary, all documents were affected by at least two challenges, and there
seems to be a long tail of infrequent exceptions or small inconsistencies that
one has to take into account in order to process such corpora correctly.

###  5.2 Query Results

In order to assess the practical benefits of our approach we implemented the
general questions presented in Table 1 as queries in the SPARQL language so we
could use a triple store (Virtuoso in our case) to automatically answer them.
The resulting SPARQL queries can be found online666https://github.com/ucds-
vu/provcorp-model/tree/master/queries. They demonstrate that our
nanopublication approach effectively merges the two corpora and allows for
information to be extracted together in a practical and efficient way. Table 3
shows the average amount of time it took to run a query, as well as the number
of rows it outputs. We managed to represent all these questions in SPARQL, and
thereby to make them automatically executable.

question | short query description | count | time
---|---|---|---
Q1 | list source and factuality value per event | 656 | 0.206s
Q2 | list events with more than one factuality value | 1,050 | 0.092s
Q3 | list factuality values per document | 194 | 0.058s
Q4 | count of FactBank source values | 425 | 0.029s
Q5 | count of FactBank events with PARC source attribution | 6 | 0.033s
Q6 | list all occurrences of “surprise” as cue | 1 | 0.048s
Table 3: SPARQL query results and average execution times to answer the
general questions Q1 to Q6

The listing below shows an example of a SPARQL query to answer one possibility
for question Q4 (“How often are certain annotation values used?”) retrieving
the count of words annotated as events from FactBank per PARC annotation
attribution type:

⬇

prefix pvcpp: <https://w3id.org/provcorp/vocab/parc/>

prefix pvcpf: <https://w3id.org/provcorp/vocab/FactBank/>

prefix oa: <http://www.w3.org/ns/oa#>

select ?Attribution (count(distinct ?word) as ?Count) where {

?event pvcpf:hasEID ?eventid.

?event oa:hasTarget ?word.

?annotation ?Attribution ?word.

values ?Attribution { pvcpp:hasContentAnnotatedWord pvcpp:hasCueAnnotatedWord
pvcpp:hasSourceAnnotatedWord }.

} group by ?Attribution

The concrete result for this query is:

⬇

Attribution Count

pvcpp:hasSourceAnnotatedWord 3

pvcpp:hasContentAnnotatedWord 284

pvcpp:hasCueAnnotatedWord 130

This thereby demonstrates how FactBank and PARC are conceptually merged and
can be queried in an integrated fashion.

As another example, the query representing question Q1 (“Who talked about an
event, and what is the factuality value of that event?”) gives us this result
(only the first four rows are shown):

⬇

textID eID eventWord factValue relativeSource sourcePhrase

https://.../wsj_0026...#text e1 said CT+ AUTHOR The White House

https://.../wsj_0026...#text e11 requested CT+ AUTHOR Timex

https://.../wsj_0026...#text e123 beneficiaries CT+ officials_AUTHOR U.S.
trade officials

https://.../wsj_0026...#text e123 beneficiaries Uu AUTHOR U.S. trade officials

...

This shows again how the annotations from both corpora can be queried
simultaneously. The result is very informative for the file wsj_0026. The
content of the columns, in order of appearance from left to right, is: the
text identifier in the form of its nanopublication URI with the suffix #text,
the event identifier of the event annotation, the word that is annotated as
the event, the factuality value of the event, the source of the event
(according to FactBank annotations), and the string in the document’s text
that represents the source (as annotated in PARC). As such, the query’s result
contains information from PARC (the source) as well as information from
FactBank (the factuality value and event). Moreover, the output of the query
allows us to see that an event can have two different FactBank sources who
each give a different factuality value to the annotated event. This is seen in
the last two rows where the event ‘beneficiaries’ has two different factuality
values, one which was given by the AUTHOR (the writer of the text document)
and another given by the ‘officials’ (a source talked about in the text
document). The different conception of ‘source’ in FactBank and PARC can also
be noted here, which shows that although annotations can be merged, the
annotation schema of each corpus should always be considered when analyzing
the results. This is also useful to reveal the representation of a corpus’s
data more easily. For example, we can see that an event from FactBank always
has an AUTHOR source.

This demonstrates how we can use the power of query languages like SPARQL to
access corpora in an integrated and fully automated way. Because the two
corpora of our case study and the annotations are now formally linked, they
are interoperable and can conceptually be seen as a single resource. Also, the
results can be exported in a variety of formats, including CSV tables and JSON
files, and be loaded and processed in other tools. It is then straightforward
to write conversion tools to other formats, such as the CoNLL format [Buchholz
and Marsi, 2006], a common practice data format used by computational
linguists. This approach ensures that the data is interoperable from the
start, and then format conversions are relatively easy as the range of nasty
interoperability challenges is already taken care of.

##  6 Discussion and Conclusion

Nanopublications have been mostly used with scientific data, such as data from
the biomedical domain [Kuhn et al., 2013]. In this work, we show that
linguistic corpora can also benefit from the fine-grained and provenance-aware
structure of nanopublications. The collection of nanopublications presented
here contains information from event annotated corpora. It is demonstrated
that when these data is modelled in a homologous way, each unique corpus can
be automatically merged in order to produce valuable data combinations that
were not easily attainable prior to the merging. Specifically, our dataset can
provide attribution annotation insight about events from FactBank.

Moreover, our nanopublications suggest the prospect of linguistic data fitting
into the Linked Data ecosystem. During the dataset creation, we were able to
reuse multiple existing Linked Data vocabularies. Linguistic data becoming
more linked would also allow it to be connected more easily with already
existing linguistic Linked Data sources from LLOD. Nevertheless, the data
format of the original annotated corpora is extremely variable, which shows in
the multiple textual challenges faced during production. While this project
only focused on two corpora, there was inconsistency in annotation format not
only between the corpora, but also within a corpus itself. Thus, the
conversion of existing linguistic corpora into a Linked Data scheme can expect
tedious pre-processing efforts. Even in our dataset, several documents needed
to be excluded for the final version. Another aspect that makes it challenging
to fit linguistic corpora in the Linked Data ecosystem relates to copyright
availability. For example, this caused us to only be able to represent part of
the PARC corpus.

In this paper, interoperability issues in linguistic data, specifically event
annotated corpora, are discussed and nanopublications are proposed as a
solution to resolve them. When one set of annotation guidelines is used to
produce annotations on one corpus, that same corpus might already have other
annotations that could be useful for the researcher. However, currently it is
very difficult for a researcher to know or retrieve the version or provenance
of these existing annotations due to poor documentation and variable
annotation formats. Aspects of nanopublications that make them useful for
annotated corpora are that they are able to be written in different formats,
they can represent versioning, and they can track provenance. Also, they
follow LLOD principles of using URIs for identification and RDF representation
as output. Above all, they seem useful for merging linguistic annotation data.
A successful model for translating existing event corpora into
nanopublications is significant not only for computational linguistics, but
also for the field of Linked Data.

## Acknowledgements

This research has been supported by the Academy Assistants Program from the
Network Insitute from the VU Amsterdam. We are grateful to Silvia Pareti for
making the PARC corpus available.

## References

  * [Bizer et al., 2011]  Christian Bizer, Tom Heath, and Tim Berners-Lee.  2011\.  Linked data: The story so far.  In Semantic services, interoperability and web applications: emerging concepts, pages 205–227. IGI Global.
  * [Bosque-Gil et al., 2015]  Julia Bosque-Gil, Jorge Gracia, John McCrae, Philipp Cimiano, Sander Stolk, Fahad Khan, Katrien Depuydt, Jesse de Does, Franscesca Frontini, and Ilja Kernerman.  2015\.  The ontolex lemon lexicography module.  W3C Community Group Final Report.
  * [Buchholz and Marsi, 2006]  Sabine Buchholz and Erwin Marsi.  2006\.  CoNLL-x shared task on multilingual dependency parsing.  In Proceedings of the Tenth Conference on Computational Natural Language Learning (CoNLL-X), pages 149–164, New York City, June. Association for Computational Linguistics.
  * [Buitelaar et al., 2011]  Paul Buitelaar, Philipp Cimiano, John McCrae, Elena Montiel-Ponsoda, and Thierry Declerck.  2011\.  Ontology lexicalisation: The lemon perspective.
  * [Chiarcos and Sukhareva, 2015]  Christian Chiarcos and Maria Sukhareva.  2015\.  Olia–ontologies of linguistic annotation.  Semantic Web, 6(4):379–386.
  * [Chiarcos et al., 2013]  Christian Chiarcos, Philipp Cimiano, Thierry Declerck, and John P McCrae.  2013\.  Linguistic linked open data (llod). introduction and overview.  In Proceedings of the 2nd Workshop on Linked Data in Linguistics (LDL-2013): Representing and linking lexicons, terminologies and other language data, pages i–xi.
  * [Chiarcos, 2012]  Christian Chiarcos.  2012\.  Interoperability of corpora and annotations.  In Linked Data in Linguistics, pages 161–179. Springer.
  * [Gangemi et al., 2003]  Aldo Gangemi, Roberto Navigli, and Paola Velardi.  2003\.  The ontowordnet project: extension and axiomatization of conceptual relations in wordnet.  In OTM Confederated International Conferences" On the Move to Meaningful Internet Systems", pages 820–838. Springer.
  * [Groth et al., 2010]  Paul Groth, Andrew Gibson, and Jan Velterop.  2010\.  The anatomy of a nanopublication.  Information Services & Use, 30(1-2):51–56.
  * [Kilgarriff, 2001]  Adam Kilgarriff.  2001\.  Comparing corpora.  International journal of corpus linguistics, 6(1):97–133.
  * [Kuhn and Dumontier, 2014]  Tobias Kuhn and Michel Dumontier.  2014\.  Trusty uris: Verifiable, immutable, and permanent digital artifacts for linked data.  In European semantic web conference, pages 395–410. Springer.
  * [Kuhn et al., 2013]  Tobias Kuhn, Paolo Emilio Barbano, Mate Levente Nagy, and Michael Krauthammer.  2013\.  Broadening the scope of nanopublications.  In Extended Semantic Web Conference, pages 487–501. Springer.
  * [Kuhn et al., 2016]  Tobias Kuhn, Christine Chichester, Michael Krauthammer, Núria Queralt-Rosinach, Ruben Verborgh, George Giannakopoulos, Axel-Cyrille Ngonga Ngomo, Raffaele Viglianti, and Michel Dumontier.  2016\.  Decentralized provenance-aware publishing with nanopublications.  PeerJ Computer Science, 2:e78.
  * [Kuhn et al., 2017]  Tobias Kuhn, Egon Willighagen, Chris Evelo, Núria Queralt-Rosinach, Emilio Centeno, and Laura I Furlong.  2017\.  Reliable granular references to changing linked data.  In International Semantic Web Conference, pages 436–451. Springer.
  * [Kuhn, 2015]  Tobias Kuhn.  2015\.  nanopub-java: A java library for nanopublications.  In Proceedings of the 5th Workshop on Linked Science 2015 — Best Practices and the Road Ahead (LISC 2015), volume 1572. CEUR-WS.
  * [Lebo et al., 2013]  Timothy Lebo, Satya Sahoo, Deborah McGuinness, Khalid Belhajjame, James Cheney, David Corsar, Daniel Garijo, Stian Soiland-Reyes, Stephan Zednik, and Jun Zhao.  2013\.  Prov-o: The prov ontology.  W3C recommendation.
  * [McGuinness et al., 2004]  Deborah L McGuinness, Frank Van Harmelen, et al.  2004\.  Owl web ontology language overview.  W3C recommendation, 10(10):2004.
  * [Menke et al., 2017]  Peter Menke, Basil Ell, and Philipp Cimiano.  2017\.  On the origin of annotations: A module-based approach to representing annotations in the natural language processing interchange format (nif).  Applied Ontology, 12(2):131–155.
  * [Pareti, 2015]  Silvia Pareti.  2015\.  Attribution: a computational approach.
  * [Pareti, 2016]  Silvia Pareti.  2016\.  Parc 3.0: A corpus of attribution relations.  In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16), pages 3914–3920.
  * [Sanderson et al., 2017]  Robert Sanderson, Paolo Ciccarese, and Benjamin Young.  2017\.  Web annotation vocabulary.  W3C recommendation.
  * [Saurí and Pustejovsky, 2009]  Roser Saurí and James Pustejovsky.  2009\.  Factbank: a corpus annotated with event factuality.  Language resources and evaluation, 43(3):227.
  * [Saurí et al., 2006]  Roser Saurí, Jessica Littman, Bob Knippen, Robert Gaizauskas, Andrea Setzer, and James Pustejovsky.  2006\.  Timeml annotation guidelines.  Version, 1(1):31.
  * [Saurı, 2008]  Roser Saurı.  2008\.  Factbank 1.0 annotation guidelines.  Ms., Brandeis University.
  * [Van Son et al., 2018]  Chantal Van Son, Oana Inel, Roser Morante, Lora Aroyo, and Piek Vossen.  2018\.  Resource interoperability for sustainable benchmarking: The case of events.  In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018).
  * [Villegas and Bel, 2015]  Marta Villegas and Núria Bel.  2015\.  Parole/simple ‘lemon’ontology and lexicons.  Semantic Web, 6(4):363–369.