# A Multilingual Corpus of Socio-political News for Event Coreference
Resolution

Ali Hürriyetoğlu$\star$, Osman Mutlu$\star$, Fatih Beyhan$\diamond$,
Fırat Duruşan$\star$, Ali Safaya$\star$, Reyyan Yeniterzi$\diamond$, Erdem
Yörük$\star$
$\star$Koç University, $\diamond$Sabancı University
<EMAIL_ADDRESS>
<EMAIL_ADDRESS>
# A Multilingual Corpus for Socio-political Event Coreference Resolution

Ali Hürriyetoğlu$\star$, Osman Mutlu$\star$, Fatih Beyhan$\diamond$,
Fırat Duruşan$\star$, Ali Safaya$\star$, Reyyan Yeniterzi$\diamond$, Erdem
Yörük$\star$
$\star$Koç University, $\diamond$Sabancı University
<EMAIL_ADDRESS>
<EMAIL_ADDRESS>
# A Multilingual Corpus for Event Coreference Resolution
for Social Sciences

Ali Hürriyetoğlu$\star$, Osman Mutlu$\star$, Fatih Beyhan$\diamond$,
Fırat Duruşan$\star$, Ali Safaya$\star$, Reyyan Yeniterzi$\diamond$, Erdem
Yörük$\star$
$\star$Koç University, $\diamond$Sabancı University
<EMAIL_ADDRESS>
<EMAIL_ADDRESS>
# Event Coreference Resolution for Contentious Politics Events

Ali Hürriyetoğlu$\star$, Osman Mutlu$\star$, Fatih Beyhan$\diamond$,
Fırat Duruşan$\star$, Ali Safaya$\star$, Reyyan Yeniterzi$\diamond$, Erdem
Yörük$\star$
$\star$Koç University, $\diamond$Sabancı University
<EMAIL_ADDRESS>
<EMAIL_ADDRESS>
###### Abstract

We propose a dataset for event coreference resolution, which is based on
random samples drawn from multiple sources, languages, and countries. Early
scholarship on event information collection has not quantified the
contribution of event coreference resolution. We prepared and analyzed a
representative multilingual corpus and measured the performance and
contribution of the state-of-the-art event coreference resolution approaches.
We found that almost half of the event mentions in documents co-occur with
other event mentions and this makes it inevitable to obtain erroneous or
partial event information. We showed that event coreference resolution could
help improving this situation. Our contribution sheds light on a challenge
that has been overlooked or hard to study to date. Future event information
collection studies can be designed based on the results we present in this
report. The repository for this study is on https://github.com/emerging-
welfare/ECR4-Contentious-Politics.

##  1 Introduction

Event databases are of great utility in research projects in various fields of
social sciences. Social actions of groups and individuals, contentious or
cooperative interactions between states and societies, and among various
social groups all manifest themselves as events. Thus, event data are crucial
in understanding a wide variety of social and political phenomena such as
modes of political participation, patterns of migration, and social and
political conflict. As any type of data that serves as a source of scientific
variables, completeness and reliability of event data have direct bearing on
the rigor of these studies. Indeed, since many sociological, political
scientific, or economic analyses that rely on event databases also inform
policy, it is arguable that quality of research has indirect bearing on the
well-being of citizens in some manner. This makes maximizing the quality of
event databases even a worthier goal.

Social scientists have long been working on creating automated event
databases. Conflict and Mediation Event Observations (CAMEO) Gerner et al.
(2002), Integrated Data for Events Analysis (IDEA) Bond et al. (2003), and
PLOVER111https://github.com/openeventdata/PLOVER, accessed on October 10,
2021. have been the main proposals of event characterizations in social
sciences. Semi-automatic Nardulli et al. (2015) and automated approaches
Leetaru and Schrodt (2013); Boschee et al. (2013); Schrodt et al. (2014);
Sönmez et al. (2016); Hürriyetoğlu et al. (2019b, a) have been developed by
adopting these formalisms.

At the same time, the NLP community has achieved some consensus on the
treatment of events both in terms of task definition and appropriate
techniques for their detection Pustejovsky et al. (2005); Doddington et al.
(2004); Song et al. (2015); Getman et al. (2018). However, in order to be
useful for social scientists, these formalisms, related language resources,
and the automated systems that realize them need to be adjusted or extended in
relation to certain cases. For instance the details of the event descriptions
and sampling of the documents in the datasets that demonstrate application of
these formalisms should reflect the richness and nuances of the events as they
are reported in various social and political contexts, dialects, and
languages. Moreover, the sampling of the documents to be annotated plays a
critical role in determining and prioritizing linguistic characteristics that
the automated approaches should handle.

The results yielded by approaches of both communities to date are either not
of sufficient quality, require tremendous effort to be replicated with both
in- and out-of- distribution data, are immeasurable in terms of quality as
there is not any gold standard list of events, or is not comparable to each
other Wang et al. (2016); Ward et al. (2013); Ettinger et al. (2017); Plank
(2016); Demarest and Langer (2018).

Any new project for creating an event database in this line still finds itself
making design decisions such as using only the heading sentences in a news
article Johnson et al. (2016) or not considering event coreference information
Boschee et al. (2013); Tanev et al. (2008) without being able to quantify the
effect of these decisions on quality of the output. Weischedel and Boschee
(2018) assume that event coreference information may not be necessary for
forecast model creation because the number of mentions in the news may already
be a useful surrogate for some forecasting models. However, the same opinion
piece was concluded by acknowledging the value of the event-event relation
information. Therefore the effect of incorporating event-event information on
use cases in social sciences domain still remains an open issue.

The event coreference, which is in-document in the scope of our study,
identification is the least studied phenomenon by both NLP and social
scientists. There are still many unknowns, which are either overlooked or
ignored, about this phenomenon Lu and Ng (2021a). More information in this
respect will enable the creation of precise and complete event databases by
decreasing the amount of duplication and partiality of event information
Zavarella et al. (2020). The following are only the first set of questions
that should be responded in order to proceed in quantifying event coreference
and improve our methodology for event information collection. What is the
number of events in a news report in average? How is the information about an
event is spread in a document? How information about multiple events co-occurs
in a report? What is the prevalence of the expressions that refer to multiple
events? How frequently sentences contain information related to multiple
events? Does occurrence of event coreference differ across languages? What is
the ratio of the documents and events that can benefit from event coreference
resolution in a random sample? How do state-of-the-art text processing tools
perform on the event coreference task? This report provides answers to
majority of these questions by providing a new event coreference corpus that
is created by exploiting news articles drawn from various contexts randomly
and using a recall-optimized active learning approach. We also demonstrate the
performance of various baseline and state-of-the-art approaches to tackle the
event coreference resolution task utilizing this corpus.

We present related work in Section 2. Next, the protest event definition, the
methodology we applied to create the corpus, and the corpus characteristics
are provided in the Sections 3, 5, and 6. The Section 4 describes the
conditions that lead us to consider events as the same or separate events. Our
effort for tackling event coreference resolution and the results are
demonstrated in the Sections 7 and 8. Finally, the Section 9 concludes this
report.

##  2 Related work

The event coreference resolution task was first introduced in the scope of MUC
6 Grishman and Sundheim (1996) and MUC 7 Chinchor (1998) as a template filling
task. Although it was not an explicitly specified task, identifying whether
events are coreferent or not was a key component in this task, as it directly
affects the number of templates to be filled. Automatic Content Extraction
(ACE 2005) dataset Doddington et al. (2004), ECB Bejan and Harabagiu (2008)
and its extended version ECB+ Cybulska and Vossen (2014), the data released at
the relatively recent evaluation campaign Knowledge Base Population (KBP)
track at Text Analysis Conference (TAC) Getman et al. (2018), OntoNotes
Pradhan et al. (2007), and Rich ERE Song et al. (2015) are the main datasets
that contain explicit annotations for event coreference. Although, many event
types are covered in these datasets, the coverage is generic in terms of event
types and the focus is on linguistic aspects of event manifestations. The
analysis of the nuances and context dependent characteristics such as the
prevalence in a random sample of news of protest events is not in the scope of
these datasets

Majority of the event coreference corpora consists of documents in English. A
few of the available datasets are mainly in English and incorporate data in
other languages such as Chinese Doddington et al. (2004); Getman et al.
(2018), Catalan Recasens et al. (2012), and Spanish Huang et al. (2016);
Getman et al. (2018) as well. 222A detailed survey of the event coreference
datasets is reported by Lu and Ng (2018).

The task event coreference resolution has not been in the scope of the studies
of the social scientists that work on automated event data collection. The few
protest event corpora proposed by Sönmez et al. (2016), Makarov et al. (2016),
and Hürriyetoğlu et al. (2021) do not include event coreference information.
The sentence level coreference information was the focus of the shared tasks
Event Sentence Coreference Identification (ESCI) in English Hürriyetoğlu et
al. (2020) and in English, Portuguese and Spanish Hürriyetoğlu et al. (2021).
Although it is about protest events, work by Huang et al. (2016) focuses only
on temporal status of the events, which can be past, on-going, and future.

We propose the first multilingual corpus for protest event coreference
resolution. The other unique features of the corpus are being based on random
sampling and active learning and containing news articles that report a single
event using a single trigger as well. These features enable us to understand
manifestation of events in a representative text collection and improve the
methodology for protest event information collection by highlighting the
importance of the event coreference in real world event information collection
studies. Last but not least, availability of this corpus will contribute to
the development and evaluation of event information collection systems usable
in real scenarios Giorgi et al. (2021).

##  3 Protest Event Definition

We define a protest as “a collective public action by a non-governmental actor
who expresses criticism or dissent and articulates a societal or political
demand” Rucht et al. (1999) (p. 68), and instances or episodes of social
conflict, which are based on grievances or aspirations to change the social
and political order. These events are referred as the “repertoire of
contention” in the scope of contentious politics Giugni (1998); Tarrow (1994)
and most similar to Sönmez et al. (2016) and Makarov et al. (2016) in the
context of our study. We operationalize this definition as contentious
politics event (CPE) and use the term protest interchangeably with it
throughout this paper.

CPEs cover any politically motivated collective action which falls outside the
official mechanisms of political participation associated with formal
government institutions of the country in which the said action takes place.
This broad event definition is developed and fleshed out on two levels. First
we identify three abstract categories of collective action, namely, political
mobilizations, social protests, and group confrontations, in order to define
the broad range of events that we focus on. Next, five specific categories of
CPEs are identified as concrete manifestations of these three modes of
collective action. Demonstrations (rallies, marches, sit-ins, slogan shouting,
gatherings etc.), industrial actions (strikes, slow-downs, picket lines,
gheraos etc.), group clashes (fights, clashes, lynching etc.), armed militancy
(attacks, bombings, assassinations etc.) and electoral politics events
(election rallies) are the concrete types of events our event ontology
encompasses.

We define criteria to which the news stories that report protest events must
conform in order to be classified as relevant. The criteria are the necessity
of civilian actors, and the existence of concrete or implied time and place
information which ascertains that the event(s) has definitely taken place.
Only reports that mention events that took place in the past, or are taking
place at the time of writing are labeled as protest news articles. The
references to the future (i.e. planned, threatened, announced or expected)
events are not labeled as protest, with the exception of threats of or
attempts at violent actions.333Although planned events and protest threats
could have a role in our analysis Huang et al. (2016), they are neither
relevant in the protest reporting context nor their prevalence, which is below
0.5% of a random sample according to our observations, allow their automated
analysis. The comparison of our definition with ACE event ontology Doddington
et al. (2004) is provided in Appendix A.

Events are annotated for their semantic types as well. The event types are

Demonstration

A demonstration is a form of political action in which a demand or grievance
is raised outside the given institutionalised forms of political participation
in a country.

Industrial action

Industrial actions are events that take place within workplaces or involve the
production process in the protest.

Group clashes

Group clashes are confrontations that stems from politicized conflicts (e.g.
identity or economic interest based or ideological conflicts) between social
groups

Armed militacy

Politically motivated violent actions that fall within our event definition
are included in this category.

Electoral politics

These events are rallies, marches or any similar mass mobilizations that are
organized within the scope of election campaigns of political parties or
leaders.

Other

Any CPE which does not fit in one of the categories listed above is marked
with this tag.

##  4 Event Separation for Coreference Annotation

If an event is referred with multiple words in a sentence, these mentions are
marked as coreferent. This is the case in Ex1 and Ex2 in Table 1. Coreferent
event mentions may occur across sentences as well, e.g. Ex3. The news articles
may report more than one event and pieces of information about one event might
not be applicable to the other event. In this case, we need to distinguish
different events within the article and link the arguments to the correct
event mentions. This is referred to as event separation and is subject to a
number of rules to ensure coherence in annotation. Note that in separating
events we need to think of the news text rather than the actual reality that
the text recounts. That is to say, we are more interested in the separate
event references in the text than whether the said events are actually
separate from each other in real life. As will be clearer in the examples
demonstrated in Table 1, sometimes it is not possible to know or show for
certain whether separate event references correspond to separate real life
events. For instance, there are two separate events in Ex4. BJP workers’
demonstration is the first event and the attack at the train station is the
second event (in the order in which they appear in the document).

Ex1: The students organized a (e1: protest) by (e1: marching) against the
payment seat decision.
---
Ex2: Commenting on the (e1: strike) which was flagged off on Monday, the union
secretary stated “(e1: it) will continue as long as our demands are not met.
Ex3: CPI(M) stages (e1: protest) rally in Bhavnagar. The Bhavnagar unit of
communist party of India CPI(m) on Friday staged a (e1: demonstration)
opposite the local post office here.
Ex4: At noon, BJP workers (e1: gathered) in the square and shouted slogans,
condemning the failure of the Union Government in delivering justice to the
victims of last year’s terror (e2: attack) at the train station where armed
militants killed 25 people.
Ex5: Karnataka State Government Employees Association organized
(e1,2:demonstrations) in Bangalore and Mysore yesterday, urging the government
not to go ahead with the new retirement scheme.

Table 1: Event coreference examples i) Ex1, Ex2, and Ex3 contain event
triggers that express the same event, ii) The triggers in Ex4 are about
separate events, and iii) The trigger in Ex5 denotes events that take place in
Bangalore and Mysore.

The separation of event references is based on difference in at least one of
the following:

Time

Events that occur at different times are separated from each other. The time
difference necessary for separation is 24 hours. Events that continue
throughout the same day are not separated even if they are reported to occur
at different times of the day.

Location

Events which are reported to take place in different locations are separated
as different events. Locations can be event places or facilities. An event
that has started at some place and continued at another, e.g. a march that
started at a location and proceeded at somewhere else, is not separated.
However, if an event is happening simultaneously at multiple locations or at
multiple locations at different times but not in continuum are separated such
that every location reference count as a separate event. Demonstrations in
Bangalore and Mysore are annotated as belonging to separate events in Ex5,
although they share the event trigger demonstration.

Participant or organizer

Events which are carried out by different participants or organizers with
separate goals and motivations are separated. This separation takes place even
in cases where different protests occur at the same time and location. The
separation is based on event motivations or goals but since motivation info is
not something that we annotate and might at times be elusive, we distinguish
events based on participants and organizers. The most frequent cases which
exemplify this situation are that of counter-protests where two groups of
participants or organizers demonstrating against each other and/or with
conflicting agendas. Note that in cases where there are multiple types of
participants and/or organizers that protest together, the event will not be
separated.

Semantic event category

Events which occur at the same time, place and facility, and organized and
participated by the same participants but have a different semantic category
are separated as different events. In other words, as a result of this, the
triggers of each event in a document that is separated by its respective event
number will have only one semantic category tag. Although this case is rare,
it can be encountered when rallies, marches or other types of demonstrations
occur during industrial strikes.

Event information can be spread over a document and occur in a sentence that
does not contain the respective event mention. This event information is not
annotated. This is to say only event information that co-occur with the
related event mention in a sentence is annotated. Moreover, there might be
event triggers (types or mentions) that are plural such as Ex5, i.e. refer to
more than one event that are separated. We have a unique procedure for
separating these events. In a nutshell, if an article contains a plural event
reference, such as “protests” which refers to e.g. two different events, each
of which are reported in the article, that article will have three separate
event numbers. This is because, the event reference "protests" is counted as
an event reference on its own.444The reason for this is that, a plural event
mention might have different arguments from the singular events that it
designates. For instance, in the sentence ”The plaza was the scene of protests
for the last two weeks” the reference ”protests” has the time argument ”last
two weeks”. The references to events that make up these ”protests” will have
their corresponding and distinct time arguments elsewhere in the article, as
in, ”last week”, and ”the week before last week”.

##  5 Methodology for Corpus Creation

A corpus that has the capacity to support creation of automated systems for
event information collection in the wild must be representative of the event
type occurrence in real life Halterman et al. (2021); Yörük et al. (2021).
Therefore, our corpus is based on a randomly sampled news articles from online
archives of local news sources from India, China, South Africa, Argentine, and
Brazil. English data was collected from The Hindu, South China Morning Post
(SCMP), New Indian Express, Indian Express, Guardian, and African News Agency
journals. The news articles in Portuguese were retrieved from Folha and
Estadao. Finally, the Spanish documents were gathered from Clarin, Pagina12,
and La Nacion. The news archives mainly cover the period between 2000 and
2019. Although the majority of the documents are from random samples, we
facilitated a high recall active sampling to extend the random samples in
cases they do not contain sufficient number of positive samples for modelling
protest events.

The annotation starts with labelling the articles as containing a protest
event or not. Next, the same procedure is applied on the sentences of the
documents that are ensured to have protest information by applying
adjudication, spotcheck, and error correction. Both at the document and
sentence levels, at least one event trigger must occur in the instance to
qualify for the positive label. The positively labeled sentences are annotated
at token level for event triggers, arguments such as time, place, and event
actors, and semantic category of these event triggers. Finally, the event
triggers are connected to each other in case they are about the same event.
Document and sentence level labelling is applied on an online tool we have
developed in-house. The event sentence grouping and token level annotations
are performed utilizing FLAT.555https://github.com/proycon/flat, accessed on
October 10, 2021.. Annotators always see complete documents and any
annotations that are agreed upon from previous level(s).

We pay particular attention to the quality of the annotations. Detailed
annotation manuals were prepared and updated as they are tested against the
data. Each annotation on an instance at any level is performed by two graduate
students who are studying social or political science and trained on the
annotation methodology. Moreover, they were trained about the socio-political
context of the country the news articles to be annotated. Therefore, if a news
article reports on an event that had not occurred in the target country, this
article is only labelled at document and sentence levels. But it is not
included in the event coreference dataset. The English text from India, China,
and South Africa was annotated by a team of annotators whose native language
is Turkish and living in Turkey. The annotations on Spanish and Portuguese
text from Argentine and Brazil respectively was prepared by a team of
annotators whose native language is Portuguese and live in Brazil.

Disagreements between annotators are adjudicated by the annotation supervisor,
who is a political scientist and responsible for maintaining annotation
manuals for each annotation task, such as document labelling, sentence
labelling, and token level event annotation. The annotation supervisor
performs a spotcheck to around 10% of the agreements. Finally, for each task
semi-automated quality checks were performed by using the adjudicated data for
both training and testing a machine learning model. The disagreements between
the predictions and annotations were analyzed by the annotation supervisor.
The quality enhancement efforts has enabled us to update around 10% of all of
the annotations.

##  6 Corpus Characteristics

The corpus consists of documents in English (EN), Portuguese (PR), and Spanish
(SE), which are represented with 896, 97, and 106 documents respectively. The
inter-annotator agreement (IAA) was measured using Krippendorf’s alpha
Krippendorff et al. (2016) for the document, sentence, and token level
annotations. Table 2 provides the average IAA scores in the rows Document,
Sentence, and Token for each language. The columns Time, Trigger, Place,
Facility, Participant, Organizer, and Target break down the average Token
scores. The IAA for event coreference annotation was measured by comparing
labels of the annotators with the adjudicated annotations using scorch - a
Python implementation of CoNLL-2012 average score for the test data (Pradhan
et al., 2014). 666https://github.com/LoicGrobol/scorch, accessed on October
28, 2021. The scores for EN, PR, and ES are 88.58, 89.72, and 68.64.

The IAA score for some of the token level annotations are relatively low. This
can be speculated to be caused by the native language of the annotators, which
is provided in the Native row in Table 2. The quality assurance steps that are
100% double annotation, adjudication of all disagreements, spotcheck of the
10% of the annotations agreed on, and semi-automated annotation error
correction ensure the low IAA scores not to affect the utilization of the
corpus.

| English | Portuguese | Spanish
---|---|---|---
Document | .75 | .82 | .83
Sentence | .65 | .72 | .79
Token | .39 | .48 | .39
Time | .59 | .52 | .53
Trigger | .38 | .44 | .45
Place | .41 | .47 | .49
Facility | .34 | .42 | .32
Participant | .36 | .51 | .39
Organizer | .45 | .67 | .26
Target | .25 | .41 | .25
Native | Turkish | Portuguese | Portuguese

Table 2: The inter-annotator agreement for document, sentence, and token
levels in terms of Krippendorff’s alpha. Token level scores are provided for
the trigger and its arguments as well. Finally, the row Native provides the
native language of the annotation teams.

Table 3 demonstrates the number of documents, sentences, and event mentions in
the rows #docs, #sents, and #events for English (EN), Portuguese (PR), and
Spanish (SE) respectively. Moreover, the Table provides information on the
amount of event information that could be identified precisely under the
assumptions  1) a document contain information about a single event,  2) a
sentence contain information about a single event, and  3) information about
an event is reported in a single sentence.  The first assumption could capture
the information presented in #docs1e which shows it holds for 532 (59.38%), 60
(61.86%), and 68 (64.15%) documents. The average number of events in a news
articles that reports a protest event is two. The second allow 3,255, 320, and
404 out of 3,559, 352, and 449 sentences to be processed based on this
assumption respectively. Around 10% of the sentences contain mentions of
multiple separate events, which is around 15% of the total event information.
The third is valid only for 763 (46%), 86 (47.77%), and 82 (44.80%) of the
events. Although the documents that contain information about a single event
are more than the ones that contain event information about multiple events,
more than half of the event information occur in documents that contain
information about multiple events.

Last but not least, the event mentions that refer to more than one event is
around 9% across all languages.

| EN | PR | SE
---|---|---|---
#docs | 896 | 97 | 105
#docs1e | 532 | 60 | 68
#sents | 13,584 | 1,397 | 2,669
#esents | 3,559 | 352 | 449
#sents1e | 3,255 | 320 | 404
#events | 1,651 | 180 | 183
#events1sent | 763 | 86 | 82

Table 3: The number of documents (#docs), sentences (#sents), and events
(#events) in English (EN), Portuguese (PR), and Spanish (SE). Documents and
sentences that contain information about one event (#docs1e and #sents1e) and
events mentioned only in one sentence (#events1sent) show the prevalence of
event coreference.

We have created train, validation, and test splits that has the ratio .70,
.15, and .15 respectively in order to facilitate experimentation,
benchmarking, and reproduciability. The splits are presented in Table 4. The
ratio, which is provided in the row Positive ratio, of the documents that
contain events is more or less the same across splits in a language.

| EN | PR | SE
---|---|---|---
#train | 628 | 67 | 74
#validation | 134 | 15 | 16
#test | 134 | 15 | 16
Positive ratio | .58 | .59 | .53

Table 4: The number of documents in the train, validation, and test splits for
English (EN), Portuguese (PR), and Spanish (ES). The ratio of the documents
that contain events is provided in the row Positive ratio.

##  7 Event Coreference Resolution Methodology

We evaluated performance of a state-of-the-art monolingual and multilingual
transformer models in an architecture proposed by Yu et al. (2020), which is
illustrated in Figure 1, on the corpus. Moreover, we have calculated a dummy
baseline score on the validation and test data. The baseline predicts all
events as being in the same cluster in a document, i.e., maximum cluster
prediction (MaxC). This baseline is the reflection of assuming a document
contains information about a single event.

Figure 1: The architecture that was proposed by Yu et al. (2020). The sentence
pairs are fed to the transformer model to get token embeddings. To obtain the
final trigger vector for a given event mention, the point-wise average of
token representations, which are part of the trigger span, is calculated.
These tokens might come from multiple words or as subtokens of a single word.
Lastly, the trigger vectors are concatenated with their point-wise
multiplication to compose the final representation of trigger pairs in
sentences i and j. The final representation is fed into a two-layer multi
layer perceptron (MLP) that yields the probability of being coreferent for a
given trigger pair.

In addition to use the standard threshold, which is .50 for predicting
coreference relation, we optimized it by evaluating all values starting from
.01 until .99 by increasing the threshold by .01 as a threshold on the
validation set for each language.

Neither the models nor the baseline fully utilize the event information that
occurs in event mentions that refer to multiple events and sentences that
contain event mentions about more than one event. The event label that occurs
more than other event labels assigned to an event mention is the final label
of the event mention. In case the occurrence frequency of the assigned event
labels are the same, the one that occurs first is used.

The sentences that contain more than 512 tokens are ignored if all event
mentions are not in the first 512 tokens. This was the case in only nine
sentence pairs in Spanish training data. 777The models we have created can be
found on
https://www.dropbox.com/sh/7j2j3f06kbn5ziv/AACVvvoFe5HH52PSKWTLph2Oa?dl=0

##  8 Results

The transformer models utilized are SpanBERT Lu and Ng
(2021b)888https://huggingface.co/SpanBERT/spanbert-base-cased, accessed on
November 15, 2021., RoBERTa Liu et al.
(2019)999https://huggingface.co/roberta-base, accessed on November 15, 2021.,
and mBERT Devlin et al. (2019)101010https://huggingface.co/bert-base-
multilingual-uncased, accessed on November 15, 2021.. The training data is set
as English and validation and test data is the respective subsets in each
language.111111Although they are not used to train the models for Portuguese
and Spanish, the splits are provided for all languages as we believe these
splits are critical for benchmarking purposes.

Table 5 demonstrates the performance of MaxC, SpanBERT, and RoBERTa on the
validation and test sets. The multilingual modeling is achieved using mBERT.
All scores are generated using a single random seed, which is 44, and measured
utilizing scorch for the scores in terms of F1, MUC, B3, CEAFe, Blanc, and
CoNLL 2012. The CoNLL 2012 score is used for comparing the systems as it is
the average of MUC, B3, and CEAFe as each of the three metrics represents a
different aspects of the performance Pradhan et al. (2012)

| thres | Validation | Test
---|---|---|---
|  | F1 | MUC | B3 | CEAFe | Blanc | CoNLL | F1 | MUC | B3 | CEAFe | Blanc | CoNLL
MaxCEN | - | 73.48 | 90.64 | 82.64 | 60.57 | 86.62 | 77.95 | 72.80 | 91.75 | 82.76 | 62.79 | 86.41 | 79.10
SpanBERT | .50 | 79.94 | 89.86 | 83.75 | 68.52 | 86.13 | 80.71 | 80.06 | 91.11 | 84.20 | 71.42 | 85.84 | 82.24
.53 | 79.71 | 90.00 | 83.93 | 69.43 | 86.07 | 81.12 | 79.95 | 90.90 | 84.13 | 71.49 | 85.96 | 82.18
RoBERTa | .50 | 80.83 | 91.07 | 84.12 | 65.99 | 87.17 | 80.39 | 81.33 | 93.04 | 85.21 | 70.20 | 88.13 | 82.82
.54 | 81.00 | 91.28 | 84.15 | 66.44 | 86.98 | 80.62 | 81.52 | 92.94 | 85.03 | 69.87 | 87.99 | 82.61
mBERTEN,EN | .50 | 77.73 | 90.51 | 83.27 | 65.19 | 85.92 | 79.66 | 80.38 | 92.14 | 84.63 | 70.05 | 86.91 | 82.27
.87 | 76.32 | 89.89 | 82.95 | 66.62 | 85.06 | 79.82 | 79.60 | 91.44 | 84.74 | 71.44 | 85.85 | 82.54
MaxCPR | - | 74.27 | 93.80 | 85.38 | 72.57 | 86.17 | 83.92 | 72.07 | 89.07 | 79.24 | 58.21 | 84.95 | 75.51
mBERTEN,PR | .50 | 78.69 | 94.64 | 86.35 | 75.88 | 86.36 | 85.62 | 77.23 | 92.03 | 84.59 | 68.66 | 87.04 | 81.76
.56 | 78.93 | 94.64 | 86.35 | 75.88 | 86.36 | 85.62 | 77.23 | 92.03 | 84.59 | 68.66 | 87.04 | 81.76
MaxCES | - | 68.92 | 89.41 | 74.93 | 45.37 | 82.63 | 69.89 | 66.86 | 91.78 | 79.39 | 58.85 | 81.95 | 76.67
mBERTEN,ES | .50 | 73.55 | 90.47 | 77.41 | 50.91 | 83.72 | 72.93 | 67.38 | 90.27 | 77.50 | 54.81 | 79.78 | 74.20
.97 | 73.86 | 89.99 | 78.74 | 52.23 | 80.78 | 73.65 | 64.44 | 88.73 | 76.32 | 54.13 | 78.63 | 73.06

Table 5: Baseline and transformer model performances for event coreference
resolution on our corpus. MaxC is the baseline calculated by assuming all
event mentions in a document refer to the same event. SpanBERT and RoBERTa are
trained and tested using respective splits of the English data. mBERT is
trained using the English training data and validated and tested on the target
language, which is Portuguese for mBERTEN,PR and Spanish for mBERTEN,ES. The
thres column is the probability threshold for determining whether two event
mentions are coreferent.

Although, RoBERTa has obtained the best CoNLL 2012 score, which is 82.82, on
the English test set, the results of SpanBERT are comparable. The threshold
optimization does not help any of these two models. The performance of
mBERTEN,EN that is trained and validated on the respective splits of the
English data is slightly higher than SpanBERT and RoBERTa. The mBERT models
that are trained on English data and validated and tested on respective splits
of Portuguese and Spanish data is reported in the rows mBERTEN,PR and
mBERTEN,ES respectively. mBERTEN,PR outperforms the baseline by obtaining
81.76 CoNLL 2012 score. However, threshold optimization on validation set does
not improve performance on test data. Finally, the performance of mBERTEN,ES
remain below the baseline even after threshold optimization.

##  9 Conclusion

We have explored the prevalence of event coreference in a random sample of
news articles collected from multiple sources, languages, and countries. We
have found that the news articles contain two events in average and state-of-
the-art transformer models can improve determination of separate events in
most of the evaluation scenarios.

We aim at tackling multilingual event coreference resolution by first testing
and improving the work reported by Phung et al. (2021) Awasthy et al. (2021),
and Tan et al. (2021) on our dataset.

## Acknowledgments

The authors from Koc University are funded by the European Research Council
(ERC) Starting Grant 714868 awarded to Dr. Erdem Yörük for his project
Emerging Welfare.

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##  Appendix A Comparison of our Protest Event Definition with ACE Event
Ontology

The ATTACK and DEMONSTRATE categories in the CONFLICT heading of the ACE
English Annotation Guidelines for Events coding manual Doddington et al.
(2004)121212https://www.ldc.upenn.edu/sites/www.ldc.upenn.edu/files/english-
events-guidelines-v5.4.3.pdf, accessed on October 10, 2021, have commonalities
with our event ontology, however, they are not applicable in the latter
setting due to fundamental differences between how events are defined in the
two annotation schemes. ACE annotation principles define events as any
“specific occurrence involving participants. An event is something that
happens” (p.5). This abstracts the actors from the definition, making event
type and sub-type definitions neutral in terms of actors. Namely, ACE event
type labels are employed based solely on the nature of the occurrences -“acts”
in relevant types- regardless of the nature of participants. On the other
hand, our event ontology focuses on CPEs, which, by their nature, involve a
particular type of actor from the outset, namely, civilian, that is non-state
actors. In this respect, the ATTACK event type, which is defined as any
“violent physical act causing harm or damage” (p.33) in ACE event coding
rules, is not applicable in CPE coding as it includes state actions, such as
international wars and military actions against non-state actors. In other
words, despite many event examples of the ATTACK type enumerated in ACE
manual, such as “attack”, “clash”, “bomb”, “explode”, overlap with our event
definition, they will be excluded from the latter when their authors are state
actors due to their different, non-contentious politics nature.

The second similar event type category in ACE event annotation guidelines is
the DEMONSTRATE category. It is defined as including events that occur
“whenever a large number of people come together in a public area to protest
or demand some sort of official action” (p.34). This definition is better
aligned with the CPE ontology we define due to the fact that it designates
actions of social and/or political actors that are non-state. However, this
definition, in itself, is too restrictive to be applicable in terms of a broad
understanding of contentious politics for two reasons. First, as it seems to
limit the scope of this event type to spontaneous (that is unorganized)
gatherings of people, it excludes certain actions of political and/or
grassroots organizations such as political parties and NGOs. Protest actions
of such organizations sometimes do not involve mass participation despite
aiming at challenging authorities, raising their political agendas or issuing
certain demands. Putting up posters, distributing brochures, holding press
declarations in public spaces are examples of such protest events. Secondly,
the requirement of mass participation in a public area leaves many protest
actions such as on-line mass petitions and boycotts, which are not necessarily
tied to specific locations where people actually gather, and actions of
individuals or small groups such as hunger strikes and self-immolation. Due to
the fundamental incompatibilities detailed above, we opted to develop a
specific event ontology and annotation guidelines131313The detailed guidelines
will be provided either as supplementary material or upon acceptance of the
paper. that are different from event definitions in ACE guidelines.

##  Appendix B Reproduciability notes

The following libraries were utilized to conduct the experiments: python ==
3.8.10, torch == 1.9.0, pytorch_lightning == 1.3.8, and transformers == 4.8.2

The following hyperparameters are optimized:

Threshold

The probability of being coreferent for two event mentions are tested from .01
to .99 by incrementally increasing the threshold by .01.

Learning Rate

Each model was trained using the learning rate of 5-e6 which was searched in
{1-e5, 5-e5, 1-e6, 5-e6, 1-e7}.

AdamW Eps

We used AdamW optimizer for our models. Eps value for our optimizer was
selected as 1-e6 which was searched in {1-e6, 1-e7, 1-e8}

Hidden Unit

Each model used used identical classifier heads which was a two-layer MLP. 128
was the selected hidden unit which was searched in 32, 64, 128, 256.

We have used fixed parameters for each model.

The number of epochs needed for each model to be trained is 2 to get shared
baseline results. The average run-time for an epoch is 10 minutes.

All experiments were performed on the same machine with 10 Intel i9-10900X
CPUs, and 2 NVIDIA RTX 2080 (8 GB) GPUs. We did not perform distributed
training among the GPUs. Full memory of a single GPU was enough to perform
each experiment.


naturally in hyperbolic band theory, like spectral networks, their associated
quiver, and the action on those quivers. It will be interesting to turn these
suggestive associations into a firmer bridge between the subjects.

######  Remark 8.

The fixed points of the torus action are uniquely described as a crystal
melting state [53]. At least _a priori_ , these crystals are unrelated to
hyperbolic crystals. Similarly, the quiver quantum mechanics problem used to
find the BPS spectrum is essentially unrelated to our quantum mechanics
problem of finding the spectrum of a Hamiltonian.

Regarding connections with quiver moduli, it is noteworthy that certain Higgs
moduli spaces — ones closely related the toy model in Section 6 — can be
obtained in at least one complex structure as Nakajima-type quiver varieties,
e.g. [15, 55]. To be more precise, the quiver variety for the so-called
“comet-shaped” quiver and an open part of the (parabolic) Higgs moduli space
for arbitrary genus and certain flag types coincide as complex varieties. Both
moduli spaces are hyperkähler but the complex-analytic isomorphism only holds
in the $I$ complex structure. The $J$ and $K$ complex structures on the quiver
side are linearizations of the (multiplicative) character variety on the Higgs
side. There is also a connection between the Hitchin integrable system and a
natural one on the quiver variety, which is roughly speaking of Gelfand-
Tsetlin type (also as described in [55]). The spectral data and integrable
system on the quiver variety may also have a band-theoretic interpretation for
both Euclidean and hyperbolic crystals, with the expectation that the
Euclidean picture will correspond with the loop-free (“star-shaped”) variety.

###  7.2. Topological materials

Topological materials have attracted a flurry of interest in recent decades
(e.g. [25]) and are, in part, an inspiration forthe more general theory of
hyperbolic matter. These topological materials, which are gapped materials
characterized by their vector bundle of eigenstates, enjoy properties that are
protected by topological invariants. Some of these invariants are necessarily
trivial in small dimensions, like the second Chern class, which is a $4$-form
and thus vanishes on the $3$-dimensional momentum space of physical Euclidean
crystals. Hyperbolic crystals have a momentum space with an arbitrarily large
dimension, so the classes of topological insulators are unrestricted. This
suggests an alternatives to constructing a model $4$-dimensional Euclidean
crystal [14], or using synthetic dimensions [66]. Two examples of hyperbolic
topological insulators were constructed in [65].

These topological invariants exist over any space parametrizing Hamiltonians.
Following the theme of this paper, we may consider these invariants over the
moduli space of Higgs bundles. This space deformation retracts to the fiber
above $0$ in the Hitchin base (the nilpotent cone), which thus encodes the
topology of the entire space. So, any topological invariant is determined from
the band structure over the nilpotent cone. In the crystal moduli
interpretation, this suggests all topological properties are measurable in the
degenerating limit of crystals.

These bulk topological insulating properties suggest a bulk-boundary
correspondence with edge states at the boundary of a hyperbolic crystal. These
have been realized in a couple of fundamental hyperbolic models [65]. The
complex momentum interpretation suggests that edge states are characterized by
Higgs bundles, as discussed in section 5.4.

###  7.3. High symmetry momenta

Physical crystals often have rich point group symmetries. Much of the standard
band theory canon focuses on band crossings at momenta fixed under large
subgroups of the point group. For hyperbolic crystals, the point group
consists of automorphisms of the associated Riemann surface [46]. These act on
vector bundles via pullback, defining automorphisms on the moduli space of
vector bundles (crystal momentum space). For degree zero line bundles, the
Torelli theorem says any polarization101010The crystallographic meaning of the
principle polarization of the Jacobian or its associated theta divisor is
still unclear. preserving automorphism of $\textrm{Jac}(\Sigma)$ comes from an
automorphism of $\Sigma$, possibly composed with the Kummer involution
$L\mapsto L^{*}$. On the Jacobian’s universal cover $\mathbb{C}^{g}$ the
Kummer involution acts by the inversion $k\mapsto-k$. On the vector potential
$A$ associated with $L$, the Kummer involution acts by $A\mapsto-A$,
representing time reversal. Since the magnetic field is zero, the Hamiltonian
is time-reversal invariant, and the Kummer involution preserves the band
structure. Its fixed points, called the Time Reversal Invariant momenta
(TRIMs) by physicists or 2-torsion points of the Jacobian by mathematicians,
play a distinguished role in band theory. On the universal cover
$\mathbb{C}^{g}$, 2-torsion points are momenta $k$ with $2k$ a lattice point,
so they are face centers of the Brillouin zone. For spin-$1/2$ systems,
Kramer’s theorem states the Hamiltonian is at least $2$-fold degenerate at
such points. We can extend these symmetries to the moduli space of Higgs
bundles ${\mathcal{M}^{\textrm{Higgs}}}$. In the crystal momentum
interpretation, each fiber is the Jacobian of a crystal, so fiberwise time-
reversal (the Kummer involution) extends to all
${\mathcal{M}^{\textrm{Higgs}}}$. For rank 2 trace-free Higgs bundles, this
acts by holomorphic involution $(E,\phi)\to(E,-\phi)$ [57]. Its fixed points
are the $SL(2,\mathbb{R})$ Higgs bundles (first described in [33, §10]),
making theses highly symmetric points of momentum space
${\mathcal{M}^{\textrm{Higgs}}}$. One connected component is the Teichmüller
section, which corresponds to a trivial line bundle on each spectral curve,
thus the zero momentum point of each Jacobian. These loci were discussed for
Euclidean crystals in Section 6.1

In general, every automorphism of the base curve gives an automorphism of the
Hitchin moduli space, whose fixed points are highly symmetric momenta. These
loci are part of an extensive line of mathematical research, see for instance
[57, 21, 9, 56, 20]. They are generally branes on
${\mathcal{M}^{\textrm{Higgs}}}$, submanifolds classified by their relation to
the three complex/kähler structures composing the hyperkähler metric on
${\mathcal{M}^{\textrm{Higgs}}}$ [31]. This symmetry is reflected in the band
structures, connecting band theory with the hyperkähler geometry of
${\mathcal{M}^{\textrm{Higgs}}}$. In view of Section 7.1, the connection with
the hyperkähler metric could interface with the work of Gaiotto, Moore, and
Neitzke.

###  7.4. Geometric Langlands correspondence

The space of abelian crystal momenta for a genus $g$ surface is a
$g$-dimensional complex torus $\textrm{Jac}(\Sigma)=\mathbb{C}^{g}/\Lambda$.
This torus is also the momentum space for the dual $2g$-dimensional real torus
$\mathbb{R}^{2g}/\Lambda^{*}$, which represents a Euclidean crystal in
$\mathbb{R}^{2g}$ with lattice $\Lambda^{*}$. This suggests an enticing
opportunity to encode a high-dimensional Euclidean crystal inside a hyperbolic
crystal. This duality has a new flavor in the crystal moduli interpretation,
which represents the space of crystal momenta with a Lagrangian torus
fibration. SYZ mirror symmetry gives a map between the moduli space of
$G$-Higgs bundles and that of ${}^{L}G$-Higgs bundle where ${}^{L}G$ is the
Langlands dual group, sending each fiber to its dual abelian variety [29, 11].
Our framework has $G=SL(n,\mathbb{C})$, but for general $G$ this map plays a
central role in the geometric Langlands correspondence [17]. Physics has
already found its way to geometric Langlands through S-duality of
$\mathcal{N}=4$ supersymmetric gauge theories [38]. The structures on each
side of the geometric Langlands correspondence are interpreted as branes on
the moduli space of Higgs bundles, mapped to one another by mirror symmetry.
Branes already arise in hyperbolic crystallography as high-symmetry crystal
momenta (Section 7.3), perhaps bringing the geometric Langlands correspondence
into hyperbolic band theory’s sphere of influence.

###  7.5. Fractional quantum Hall states

With the basic framework of hyperbolic band theory established, the logical
next step is to apply a magnetic field [64, 37, 1]. Our techniques should
carry over without much trouble to integer quantum Hall states, where the
magnetic flux through a unit cell is an integer multiple $N_{B}$ of the
hyperbolic area. The magnetic field replaces degree zero bundles with degree
$N_{B}$ bundles. (Alternatively, vector bundles of nonzero degree arise from
projective unitary representations of the fundamental group [3], relating to
the magnetic translation operators constructed in [1].) Fractional quantum
Hall (FQH) states (where flux per area is rational) are trickier, necessarily
requiring multi-particle interacting states. One approach uses approximate
ground states called Laughlin wavefunctions, which capture the qualitative
aspects of FQH states, like quasiparticles with fractional statistics. On
compact Riemann surfaces, Laughlin states are holomorphic sections of a line
bundle on the $n$th symmetric product of the surface [40, 41]. This line
bundle is twisted by the $n$th exterior tensor product of an abelian crystal
momentum [42], fitting Laughlin wavefunctions into the framework of hyperbolic
band theory. What about nonabelian crystal momenta? Perhaps these correspond
to nonabelian FQH states on $\Sigma$, where the quasiparticles are vector-
valued. These are best described with an effective Chern-Simons theory on
$\Sigma$. Nonabelian Laughlin wavefunctions are the conformal blocks of a
Chern-Simons theory [48]. The space of conformal blocks is isomorphic to the
holomorphic sections of the prequantum line bundle over the Chern-Simons phase
space [58], which is diffeomorphic to the moduli space of trace-free Higgs
bundles (for complex C-S theory). The holomorphic sections of the prequantum
line bundle are nonabelian theta functions, which restrict to ordinary theta
functions on each fiber [5].

The relationship with Higgs bundles extends to effective field theory
interpretations of FQH states. Quasiparticles of these theories are solutions
to a vortex equation, which arise from Hitchin equations on subsets of the
moduli space of Higgs bundles (for example, the abelian vortex equations are
Hitchins equations on the Teichmüller component [33, §11]). These effective
field theories have a particle-vortex duality, replacing vortex solutions with
fundamental fields and vice versa. This is a version of the S-duality of
Chern-Simons theory, which manifests the geometric Langlands correspondence
[38], and relates the integer and quantum Hall effects [36, 35]. Connecting
with Section 7.4, perhaps two hyperbolic particle-vortex dual states are
related by mirror symmetry of the moduli of Higgs bundles.

There are seemingly two ways to obtain FQH states on hyperbolic crystals. We
can follow physics by considering interacting multi-particle states and
studying their effective field theory. On the other hand, we can construct
families of crystals from spectral covers then construct theta functions on
each crystal’s Jacobian, and then finally glue these together to a nonabelian
theta function on Hitchin moduli space. Guided by aesthetic sensibilities, we
guess that the resulting states are in some sense the same. (The
crystallographic interpretation of theta functions is, itself, an intriguing
open question.)

###  7.6. Putting everything together

The objects of our speculations already weave together into a well-connected
web (Figure 13, black lines). We suggested how hyperbolic matter ties in with
each (Figure 13, blue lines), and one can guess at the overall connectivity of
this picture. Above, we speculated that both paths from the center to
fractional quantum Hall states are somehow equivalent. It would be intriguing
if this held more generally for every path through the web. For instance, one
may hope that the high-symmetry branes in ${\mathcal{M}^{\textrm{Higgs}}}$
agree with the asymptotic hyperkähler structure seen in the semiclassical
large complex crystal momentum limit. At the same time, high-symmetry branes
may map to one another as the Jacobian maps to the dual position space
crystal, reflecting the geometric Langlands correspondence. Further still,
this map may relate two families of hyperbolic crystals, whose associated
fractional quantum hall states are related by particle-vortex duality — which
is to say that perhaps Figure 13 commutes.

Figure 13. Flowchart summarizing the speculated connections between hyperbolic
matter and various other objects (blue lines). It also shows preexisting
connections between these objects (black lines). Most of these connections
were woven by the character at the center of the web, namely Higgs bundles.

The only evidence so far is aesthetic, and so we cannot call this a conjecture
in good conscience. Instead, we conclude with:

######  Daydream 1.

This diagram commutes.

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