Call for workshop papers and Shared Task participation: the 6th workshop on
Challenges and Applications of Automated Extraction of Socio-political
Events from Text - CASE @ RANLP 2023
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URL: https://emw.ku.edu.tr/case-2023/
Paper submission deadline: 10 July 2023
Paper acceptance notification: 5 August 2023
Paper camera-ready: 25 August 2023
Workshop dates: 7-8 September 2023
Dates and deadlines for the shared task are below.
Softconf page of the workshop: https://softconf.com/ranlp23/CASE/
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We invite contributions from researchers in computer science, NLP, ML, DL,
AI, socio-political sciences, conflict analysis and forecasting, peace
studies, as well as computational social science scholars involved in the
collection and utilization of socio-political event data. This includes
(but is not limited to) the following topics
1) Extracting events and their arguments such as time and location in and
beyond a sentence or document, event coreference resolution.
2) Research in NLP technologies in relation to event detection: geocoding,
temporal reasoning, argument structure detection, syntactic and semantic
analysis of event structures, text classification, for event type
detection, learning event-related lexica, event co-reference resolution,
fake news analysis, and others with a focus on real or potential event
detection applications.
3) New datasets, training data collection, and annotation for event
information.
4) Event-event relations, e.g., subevents, main events, spatio-temporal
relations, causal relations.
5) Event dataset evaluation in light of reliability and validity metrics.
6) Defining, populating, and facilitating event schemas and ontologies.
7) Automated tools and pipelines for event collection related tasks.
8) Lexical, syntactic, semantic, discursive, and pragmatic aspects of event
manifestation.
9) Methodologies for development, evaluation, and analysis of event
datasets.
10) Applications of event databases, e.g. early warning, conflict
prediction, policymaking.
11) Estimating what is missing in event datasets using internal and
external information.
12) Detection of new and emerging SPE types, e.g. creative protests.
13) Release of new event datasets.
14) Bias and fairness of the sources and event datasets.
15) Ethics, misinformation, privacy, and fairness concerns pertaining to
event datasets.
16) Copyright issues on event dataset creation, dissemination, and sharing.
17) Cross-lingual, multilingual and multimodal aspects in event analysis.
18) Resources and approaches related to contentious politics around climate
change.
**** Shared tasks ****
Please check the workshop page and Github repositories of the respective
task for additional details.
Task 1 - Multilingual protest news detection:
The performance of an automated system depends on the target event type as
it may be broad or potentially the event trigger(s) can be ambiguous. The
context of the trigger occurrence may need to be handled as well. For
instance, the ‘protest’ event type may be synonymous with ‘demonstration’
or not in a specific context. Moreover, hypothetical cases such as future
protest plans may need to be excluded from the results. Finally, the
relevance of a protest depends on the actors as in a contentious political
event only citizen-led events are in the scope. This challenge becomes even
harder in a cross-lingual and zero-shot setting in case training data are
not available in new languages. We tackle the task in four steps and hope
state-of-the-art approaches will yield optimal results.
Contact person: Ali Hürriyetoğlu (ali.hurriyetoglu(a)gmail.com)
Github: https://github.com/emerging-welfare/case-2022-multilingual-event
Task 2 - Collecting and Geocoding Armed Clash Events in Russian Ukrainian
Conflict:
There is a mismatch between the event information collected between
automated and manual approaches. We aim at identifying similarities and
differences between the results of these paradigms for creating event
datasets. The participants of Task 1 will be invited to run the systems
they will develop to tackle Task 1 on a text archive. Participation in Task
1 is not a precondition to participate in Task 2.
Contact person: Hristo Tanev (htanev(a)gmail.com) and Onur Uca (
onuruca(a)mersin.edu.tr)
Github: https://github.com/zavavan/case2023_task2
Task 3 - Event causality identification:
Causality is a core cognitive concept and appears in many natural language
processing (NLP) works that aim to tackle inference and understanding. We
are interested in studying event causality in news, and therefore,
introduce the Causal News Corpus. The Causal News Corpus consists of 3,767
event sentences, extracted from protest event news, that have been
annotated with sequence labels on whether it contains causal relations or
not. Subsequently, causal sentences are also annotated with Cause, Effect
and Signal spans. Our subtasks work on the Causal News Corpus, and we hope
that accurate, automated solutions may be proposed for the detection and
extraction of causal events in news.
Contact person: Fiona Anting Tan (tan.f(a)u.nus.edu)
Github: https://github.com/tanfiona/CausalNewsCorpus
Task 4 - Multimodal Hate Speech Event Detection:
Hate speech detection is one of the most important aspects of event
identification during political events like invasions. In the case of hate
speech detection, the event is the occurrence of hate speech, the entity is
the target of the hate speech, and the relationship is the connection
between the two. Since multimodal content is widely prevalent across the
internet, the detection of hate speech in text-embedded images is very
important. Given a text-embedded image, this task aims to automatically
identify the hate speech and its targets. This task will have two subtasks.
Contact person: Surendrabikram Thapa (surendrabikram(a)vt.edu)
Github: https://github.com/therealthapa/case2023_task4
**** Deadlines for the Shared tasks ****
** Task 1, 3, 4:
Training & Validation data available: May 1, 2023
Test data available: Jun 15, 2023
Test start: Jun 15, 2023
Test end: Jun 30, 2023
System Description Paper submissions due: Jul 10, 2023
Notification to authors after review: Aug 5, 2023
Camera ready: Aug 25, 2023
** Task 2:
Sample Text archive is available: May 22, 2023
Text archive for evaluation is available: July 1, 2023
Evaluation period starts: July 1, 2023
Evaluation period ends: July 24, 2023
System Description Paper submissions due: July 31, 2023
Notification to authors after review: August 7, 2023
Camera ready: August 25, 2023
*** Keynotes ***
We will continue our tradition of inviting keynote speakers from both
social and computational sciences. The social science keynote will be
delivered by Erdem Yörük with the title “Using Automated Text Processing to
Understand Social Movements and Human Behaviour” and the computational ones
will be delivered by Ruslan Mitkov and Kiril Simov.
Please see the workshop webpage (https://emw.ku.edu.tr/case-2023/) for
additional details.
The Department of Translation and Language Sciences
<https://www.upf.edu/en/dtcl> of Universitat Pompeu Fabra
<https://www.upf.edu/> (Barcelona) is seeking to fill a tenure-track *faculty
position <https://apply.interfolio.com/125314> *in the area of *Translation
Studies and English Language*. Duties include research and knowledge
transfer, teaching, and administrative service. Research areas associated
with the position:
- Technological applications and innovation for language learning and
translator training, including but not limited to resources and
applications for classroom use, corpora resources, writing assistants,
intelligent tutoring systems, digital dictionaries and/or educational data
mining;
- Communicative skills for transferring research outcomes to the
academic community as well as society at large.
Application *deadline*: July 8 2023
More information: https://apply.interfolio.com/125314
Gemma Boleda
Universitat Pompeu Fabra / ICREA
https://gboleda.github.io
Dear colleague,
This is the final call for abstracts for CLIN33, which will be held in Antwerp (Belgium), September 22nd 2023. We accept abstracts describing work on any aspect of computational linguistics / natural language processing (finished or in progress). Submissions must be written in English and submitted through this web form<https://docs.google.com/forms/d/e/1FAIpQLSf912QGdJYjgsuSRqqJ6uaLqYLhVXtW-ZP…> by June 15th 2023. Notifications of acceptance will be sent out on July 15th 2023 and authors of accepted abstracts will have the opportunity to submit a full paper after the conference to CLIN Journal.
Those who are interested in participating in this year's shared task can find more information on the dedicated shared task website<https://sites.google.com/view/shared-task-clin33/home>.
Registrations<https://forms.uantwerpen.be/en/faclw/registration-clin33/> for the event are open and have to be completed before September 5th 2023.
For more info, please visit the CLIN33 website: https://clin33.uantwerpen.be/
We are looking forward to welcoming you!
The CLIN33 organizers
CLiPS
University of Antwerp
We are delighted to invite you to an afternoon of public lectures on language technology and its interaction with society. The lectures will take place in Auditorium 4 at the IT University of Copenhagen on 13 June 2023, from 14:30 to 16:45 (UTC+2). Attendance is free for anyone interested.
The lectures will also be streamed on Zoom. For remote participation, please register here:
https://itucph.zoom.us/meeting/register/u5Utf-Chrz0sHNYzd76DD9WjJpOU0CckVsMb
Speakers and titles:
- Luca Maria Aiello, IT University of Copenhagen: The Language of Coordination
- Shashi Narayan, Google London: Introducing Text-blueprint: Conditional generation with question-answering plans
- Anne Lauscher, University of Hamburg: Ethical conversational AI - Searching for the truth?
Abstracts and further information can be found here:
https://christianhardmeier.rax.ch/workshop/langtech-society-2023/
--
Christian Hardmeier, Associate Professor – https://christianhardmeier.rax.ch/
IT University of Copenhagen, Department of Computer Science
CoCo4MT Shared Task: First Call for Participation
We are excited to introduce a new shared task for this year’s CoCo4MT
workshop! Our aim is to encourage and facilitate research on corpus
construction for low-resource machine translation.
Corpus creation for machine translation is typically constrained by the
cost and availability of human translators. When a new dataset needs to be
created for a low-resource language or a specialized domain, the annotation
budget should be used efficiently and any sentences chosen for translation
should be of high quality and as useful for machine translation system
training as possible.
In this shared task, we ask participants to come up with ways in which such
examples can be identified for a target language without any existing data.
Specifically, given a parallel corpus between high-resource languages, the
goal is to choose a good subset of the high-resource corpus to be
translated into the low-resource language, in order to obtain a good
training set for a machine translation system. The shared task winner will
be the team whose instances result in the best final system after training.
Detailed information: https://sites.google.com/view/coco4mt/shared-task
Registration: https://forms.gle/jfKSPQMKEmaaXFHy5
Important Dates
- May 19 2023: Release of train, dev and test data
-
May 30 2023: Release of baselines
-
July 12, 2023: Deadline to submit results
-
July 20, 2023: System description papers due
Organizers (listed alphabetically)
-
Ananya Ganesh, University of Colorado Boulder
-
Constantine Lignos, Brandeis University
-
John E. Ortega, Northeastern University
-
Jonne Sälevä, Brandeis University
-
Katharina Kann, University of Colorado Boulder
-
Marine Carpuat, University of Maryland
-
Rodolfo Zevallos, Universitat Pompeu Fabra
-
Shabnam Tafreshi, University of Maryland
-
William Chen, Carnegie Mellon University
--
Dr. Katharina Kann
Assistant Professor of Computer Science
University of Colorado Boulder
Personal page: https://kelina.github.io
Group page: https://nala-cub.github.io
==================================================
*CFP: ML/NLP Competition on Automatic Classification of Literary Epochs
(CoLiE)*
To advance the field of implicit temporal information retrieval from a
text, this competition aims to challenge participants to develop automatic
methods to identify the literary epochs of a given text, which is
considered here as an implicit temporal context of a book.
The task on Automatic Classification of Literary Epochs (CoLiE) aims at
automatic identification of the literary epoch of a given text from its
writing style: (1) Romanticism (1798-1837), (2) Victorian Literature
(1837-1901), (3) Modernism (1900-1945), (4) Postmodernism (1945-2000), and
(5) our days (from 2000).
The competition is held as a part of the IACT’23
<https://en.sce.ac.il/news/iact23> workshop, held on July 27, 2023, in
conjunction with the 46th International ACM SIGIR Conference on Research
and Development in Information Retrieval
This competition is open to anyone with a passion for information
retrieval, machine learning, and natural language processing. Whether you
are a seasoned expert or a newcomer to the field, we welcome you to
participate and extend the boundaries of automated text analysis!
Competition site: http://www.kaggle.com/competitions/colie
Competition Timeline
- May 28, 2023: The competition is open to participants. Training and
validation sets together with their labels are available.
- July 10, 2023: Test dataset available.
- July 17, 2023, 23:59 UTC: Final submission deadline.
- July 27, 2023: The winners are announced at the special session at the
IACT'23 <https://en.sce.ac.il/news/iact23> workshop.
*The organizing team*
- Dr. Marina Litvak (marinal(a)ac.sce.ac.il),
Software Engineering Department,
Shamoon College of Engineering, Beer Sheva,
84100, Israel
- Dr. Irina Rabaev (irinar(a)ac.sce.ac.il),
Software Engineering Department,
Shamoon College of Engineering, Beer Sheva,
84100, Israel
- Prof. Ricardo Campos (ricardo.campos(a)ipt.pt),
Ci2 - Smart Cities Research Center, Polytechnic Institute of Tomar
INESC TEC, Porto
Porto, Portugal
- Prof. Alípio Mário Jorge (amjorge(a)fc.up.pt)
University of Porto
Porto, Portugal
- Prof. Adam Jatowt (adam.jatowt(a)uibk.ac.at)
University of Innsbruck,
Innsbruck, Austria
- Mr. Vladimir Younkin (vladiyo(a)ac.sce.ac.il),
Software Engineering Department,
Shamoon College of Engineering, Beer Sheva,
84100, Israel
--
Best regards,
Marina Litvak
On behalf of Dr. Elliot Crowley from the School of Engineering at the University of Edinburgh (queries at elliot.crowley(a)ed.ac.uk):
Application link: Affordable Training of Large Language Models<https://www.eng.ed.ac.uk/studying/postgraduate/research/phd/affordable-trai…>
Recent developments in large language models (LLMs) have caught the attention of the public. LLMs such as OpenAI's GPT-4 and Google's Bard are able to generate remarkably realistic, coherent text based on a user's input and have the potential to be general-purpose tools used throughout society e.g. for customer service, summarising text, answering questions, writing contracts or translating between languages.
However, LLMs are prohibitively expensive to train. GPT-3 (which is significantly smaller than its successor, GPT-4) has an estimated training time of 355-GPU years and an estimated training cost of $4.6M [1]. Only large, wealthy institutions can train these models and thereby control how they are trained and who gets access to them. This is undemocratic.
Very recent work provides hope however. In [2] the authors explore the promising idea of “cramming”: the training of a LLM on a single GPU in a day. In [3] the authors use synthetic data to train “small” language models that can produce consistent stories at little cost. There is a huge discrepancy in quality between these models and their expensive counterparts, however.
In this PhD, the student will investigate affordable LLM training i.e. with limited compute and/or data, inspired by [2,3]. Avenues of research could include (i) generating training data that facilitates fast training e.g. through dataset distillation [4]; (ii) exploring neural architecture search to develop models that are "aware" of being resource-constrained while being trained; (iii) developing novel cost-effective training algorithms, (iv) leveraging and tuning open-source LLMs.
The successful student will have opportunities for collaboration within and outside Edinburgh’s School of Engineering e.g. with colleagues in the Institute for Digital Communications<https://www.eng.ed.ac.uk/research/institutes/idcom/>, The Bayesian and Neural Systems Group<https://www.bayeswatch.com/>, and Edinburgh NLP<https://edinburghnlp.inf.ed.ac.uk/>.
[1] https://lambdalabs.com/blog/demystifying-gpt-3
[2] https://arxiv.org/abs/2212.14034
[3] https://arxiv.org/abs/2305.07759
[4] https://arxiv.org/abs/1811.10959
The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. Is e buidheann carthannais a th’ ann an Oilthigh Dhùn Èideann, clàraichte an Alba, àireamh clàraidh SC005336.
*** Final Call for Submissions ***
10th European Conference On Service-Oriented And Cloud Computing (ESOCC 2023)
October 24-26, 2023, Golden Bay Beach Hotel, Larnaca, Cyprus
https://cyprusconferences.org/esocc2023/
(Proceedings to be published in Springer LNCS;
Journal Special Issue with Springer Computing)
Submission Deadline: Abstracts by June 25, 2023; Full Papers by July 2, 2023
AIM AND SCOPE
Nowadays, Service-Oriented and Cloud Computing are the primary approaches to build
large-scale distributed systems and deliver software services to end users. Cloud-native
software is pervading the delivery of enterprise applications, as they are composed of
(micro)services that can be independently developed and deployed by exploiting multiple
heterogeneous technologies. Resulting applications are polyglot service compositions that can
then be shipped in serverful or serverless platforms (e.g., using virtualization technologies).
These characteristics make Service-Oriented and Cloud Computing the natural answers for
fulfilling the industry’s need for flexibly scalable and maintainable enterprise applications, to
be delivered through state-of-the-art methodologies, like DevOps. To further support this,
researchers and practitioners need to create methods, tools and techniques to support
cost-effective and secure development as well as use of dependable devices, platforms,
services and service-oriented applications in the Cloud, now also considering the Cloud-IoT
computing continuum to exploit widespread adoption of smart connected things and the
increasing growth of their computing capabilities.
The European Conference on Service-Oriented and Cloud Computing (ESOCC) is the premier
conference on advances in the state-of-the-art and practice of Service-Oriented Computing
and Cloud Computing in Europe. ESOCC aims to facilitate the exchange between researchers
and practitioners in the areas of Service-Oriented Computing and Cloud Computing, as well as
to explore the new trends in those areas and foster future collaborations in Europe and beyond.
TOPICS OF INTEREST
ESOCC 2023 seeks original, high-quality contributions related to all aspects of Service-Oriented
and Cloud computing. Specific topics of interest include, but are not limited to: • Applications for Service-Oriented and Cloud Computing, e.g., big data, commerce, energy,
finance, health, scientific computing, smart cities • Blockchains for Service-Oriented and Cloud Computing • Business aspects of Service-Oriented and Cloud Computing, e.g., business models,
brokerage, marketplaces, costs, pricing • Business processes, e.g., service-based workflow deployment and management • Cloud interoperability, service and Cloud standards, • Cloud-IoT computing continuum, e.g., edge computing, fog computing, mobility computing,
next generation services/IoT • Cloud-native architectures and paradigms, e.g., microservices and DevOps • Cloud service models, e.g., IaaS, PaaS, SaaS, DBaaS, FaaS, etc. • Deployment, composition, and management of applications in Service-Oriented and Cloud
Computing • Foundations and formal methods for Service-Oriented and Cloud Computing • Enablers for Service-Oriented and Cloud Computing, e.g., service discovery, orchestration,
matchmaking, monitoring, and analytics • Model-Driven Engineering for Service-Oriented and Cloud Computing • Multi-Cloud, cross-Cloud, and federated Cloud solutions • Requirements engineering, design, development, and testing of applications in
Service-Oriented and Cloud Computing • Semantic services and service mining • Service and Cloud middlewares and platforms • Software/service adaptation and evolution in Service-Oriented and Cloud Computing • Storage, computation and network Clouds • Sustainability and energy issues in Service-Oriented and Cloud Computing • Quality aspects (e.g., governance, privacy, security, and trust) of Service-Oriented and Cloud
Computing • Quality of Service (QoS) and Service-Level Agreement (SLA) for Service-Oriented and Cloud
Computing • Social aspects of Service-Oriented and Cloud Computing, e.g., crowdsourcing services, social
and crowd-based Clouds • Virtualization for Service-Oriented and Cloud Computing, e.g., serverless, container-based
virtualization, VMs
IMPORTANT DATES
• Submission of abstracts: June 25th, 2023 (AoE) • Submission of full papers: July 2nd, 2023 (AoE) • Notification to authors: August 4th, 2023 (AoE) • Camera-ready versions due: August 21st, 2023 (AoE)
• Author registration due: August 21st, 2023 (AoE)
TYPES OF SUBMISSIONS
ESOCC 2023 invites submissions of the following kinds: • Regular Research Papers (15 pages including references) • PhD Symposium (12 pages including references) • Projects and Industry Reports (Projects and Industry Reports (1 to 6 pages including
references, describing an ongoing EU or national project, or providing industrial perspectives
on innovative applications, technologies, or methods in ESOCC’s scope)
We only accept original papers, not submitted for publication elsewhere. The papers must be
formatted according to the proceedings guidelines of Springer’s Lecture Notes in Computer
Science (LNCS) series (http://www.springer.com/lncs).
They must be submitted to the EasyChair site at: https://easychair.org/conferences/?conf=esocc2023 by selecting the right track.
Accepted papers from all tracks will be published in the main conference proceedings by
Springer in the LNCS series. For publication to happen, at least one author of each accepted
paper is expected to register and present the work at the conference.
The best papers accepted will be invited to submit extended versions for a Journal Special
Issue to be published by Springer Computing.
ORGANISATION
General Chair
• George A. Papadopoulos, University of Cyprus, CY
(george at ucy.ac.cy)
Program Chairs
• Florian Rademacher, University of Applied Sciences and Arts Dortmund, DE
(florian.rademacher at fh-dortmund.de) • Jacopo Soldani, University of Pisa, IT
(jacopo.soldani at unipi.it)
Steering and Program Committee
https://cyprusconferences.org/esocc2023/committees/
The University of Bologna is offering* a funded residential bootcamp*:
*"Theories and methods for the corpus-assisted analysis of discourse: from
language that denotes to language that expresses phenomena". *
20 participants
*27-30 September (Bertinoro - Italy)*
*Deadline for application 19/06/2023*
#cadscamp
All info:
*https://centri.unibo.it/colitec/en/events/bootcamp-28-30-september-2023
<https://centri.unibo.it/colitec/en/events/bootcamp-28-30-september-2023> *
Best,
Anna
Call for Participation:
*FinCausal-2023 Shared Task: “Financial Document Causality Detection” *is
organised within the *5th Financial Narrative Processing Workshop (FNP
2023)* taking place in the 2023 IEEE International Conference on Big Data
(IEEE BigData 2023) <http://bigdataieee.org/BigData2023/>, Sorrento, Italy,
15-18 December 2023. It is a *one-day event*. The exact date is to be
announced.
Important Dates:
- Call for participation and registration: 3rd June 2023
- Registration deadline: 28 June
- Training set release: 29 June 2023
- Test set release: 5 September 2023
- Systems submission deadline: 15 September 2023
- Release of results: 20 September 2023
- Paper submission deadline: 20 October 2023
- Notification of acceptance: November 12, 2023
- Camera-ready of accepted papers: November 20, 2023
- FNP Workshop: December 2023
Workshop URL: https://wp.lancs.ac.uk/cfie/fincausal2023/
Registration Form: https://forms.gle/29E161a8RmMosBLU8. After completing
the registration form, the practice set will be sent to participants.
*Shared Task Description:*
Financial analysis needs factual data and an explanation of the variability
of these data. Data state facts but need more knowledge regarding how these
facts materialised. Furthermore, understanding causality is crucial in
studying decision-making processes.
The *Financial Document Causality Detection Task* (FinCausal) aims at
identifying elements of cause and effect in causal sentences extracted from
financial documents. Its goal is to evaluate which events or chain of
events can cause a financial object to be modified or an event to occur,
regarding a given context. In the financial landscape, identifying cause
and effect from external documents and sources is crucial to explain why a
transformation occurs.
Two subtasks are organised this year. *English FinCausal subtask *and* Spanish
FinCausal subtask*. This is the first year where we introduce a subtask in
Spanish.
*Objective*: For both tasks, participants are asked to identify, given a
causal sentence, which elements of the sentence relate to the cause, and
which relate to the effect. Participants can use any method they see fit
(regex, corpus linguistics, entity relationship models, deep learning
methods) to identify the causes and effects.
*English FinCausal subtask*
- *Data Description: *The dataset has been sourced from various 2019
financial news articles provided by Qwam, along with additional SEC data
from the Edgar Database. Additionally, we have augmented the dataset from
FinCausal 2022, adding 500 new segments. Participants will be provided with
a sample of text blocks extracted from financial news and already labelled.
- *Scope: *The* English FinCausal subtask* focuses on detecting causes
and effects when the effects are quantified. The aim is to identify, in
a causal sentence or text block, the causal elements and the consequential
ones. Only one causal element and one effect are expected in each segment.
- *Length of Data fragments: *The* English FinCausal subtask* segments
are made up of up to three sentences.
- *Data format: *CSV files. Datasets for both the English and the
Spanish subtasks will be presented in the same format.
This shared task focuses on determining causality associated with a
quantified fact. An event is defined as the arising or emergence of a new
object or context regarding a previous situation. So, the task will
emphasise the detection of causality associated with the transformation of
financial objects embedded in quantified facts.
*Spanish FinCausal subtask*
- *Data Description: *The dataset has been sourced from a corpus of
Spanish financial annual reports from 2014 to 2018. Participants will be
provided with a sample of text blocks extracted from financial news,
labelled through inter-annotator agreement.
- *Scope: *The *Spanish FinCausal subtask* aims to detect all types of
causes and effects, not necessarily limited to quantified effects. The
aim is to identify, in a paragraph, the causal elements and the
consequential ones. Only one causal element and one effect are expected in
each paragraph.
- *Length of Data fragments: *The *Spanish FinCausal subtask* involves
complete paragraphs.
- *Data format: *CSV files. Datasets for both the English and the
Spanish subtasks will be presented in the same format.
This shared task focuses on determining causality associated with both
events or quantified facts. For this task, a cause can be the justification
for a statement or the reason that explains a result. This task is also a
relation detection task.
*FinCausal Shared Task Organisers:*
- Antonio Moreno-Sandoval (UAM, Spain)
- Blanca Carbajo Coronado (UAM, Spain)
- Doaa Samy (UCM, Spain)
- Jordi Porta (UAM, Spain)
- Dominique Mariko (Yseop, France)
For any questions, please contact the organisers at *fincausal.2023(a)gmail.com
<fincausal.2023(a)gmail.com>*