Challenges and applications of automated extraction of socio-political events from text (CASE 2023): Workshop and shared task report
We provide a summary of the sixth edition of the CASE workshop that is held in the scope of
RANLP 2023. The workshop consists of regular papers, three keynotes, working papers of …
RANLP 2023. The workshop consists of regular papers, three keynotes, working papers of …
Exploring causal learning through graph neural networks: an in-depth review
In machine learning, exploring data correlations to predict outcomes is a fundamental task.
Recognizing causal relationships embedded within data is pivotal for a comprehensive …
Recognizing causal relationships embedded within data is pivotal for a comprehensive …
Maven-ere: A unified large-scale dataset for event coreference, temporal, causal, and subevent relation extraction
The diverse relationships among real-world events, including coreference, temporal, causal,
and subevent relations, are fundamental to understanding natural languages. However, two …
and subevent relations, are fundamental to understanding natural languages. However, two …
Document-level relation extraction with hierarchical dependency tree and bridge path
The inter-sentence relation in a document is characterized by complex contextual
information, large span of correlation and many kinds of relations, leading to the poor effect …
information, large span of correlation and many kinds of relations, leading to the poor effect …
Event Causality Identification with Causal News Corpus--Shared Task 3, CASE 2022
The Event Causality Identification Shared Task of CASE 2022 involved two subtasks
working on the Causal News Corpus. Subtask 1 required participants to predict if a sentence …
working on the Causal News Corpus. Subtask 1 required participants to predict if a sentence …
Discriminative reasoning with sparse event representation for document-level event-event relation extraction
Abstract Document-level Event-Event Relation Extraction (DERE) aims to extract relations
between events in a document. It challenges conventional sentence-level task (SERE) with …
between events in a document. It challenges conventional sentence-level task (SERE) with …
Identifying conspiracy theories news based on event relation graph
Conspiracy theories, as a type of misinformation, are narratives that explains an event or
situation in an irrational or malicious manner. While most previous work examined …
situation in an irrational or malicious manner. While most previous work examined …
Extended Multilingual Protest News Detection--Shared Task 1, CASE 2021 and 2022
We report results of the CASE 2022 Shared Task 1 on Multilingual Protest Event Detection.
This task is a continuation of CASE 2021 that consists of four subtasks that are i) document …
This task is a continuation of CASE 2021 that consists of four subtasks that are i) document …
Seag: Structure-aware event causality generation
Extracting event causality underlies a broad spectrum of natural language processing
applications. Cutting-edge methods break this task into Event Detection and Event Causality …
applications. Cutting-edge methods break this task into Event Detection and Event Causality …
A review and roadmap of deep learning causal discovery in different variable paradigms
Understanding causality helps to structure interventions to achieve specific goals and
enables predictions under interventions. With the growing importance of learning causal …
enables predictions under interventions. With the growing importance of learning causal …