# Event Causality Identification with Causal News Corpus -- Shared Task 3, CASE 2022

arXiv: https://arxiv.org/abs/2211.12154 · HTML: https://mlsanity.com/paper/2211.12154/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 23 of its 69 references that are in the map.
- First posted on arXiv 22 Nov 2022.

## Builds on (most cited first, 23 of 23)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter](https://mlsanity.com/paper/1910.01108/) (2019)
- [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://mlsanity.com/paper/2006.03654/) (2020)
- [SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations Between Pairs of Nominals](https://mlsanity.com/paper/1911.10422/) (2019)
- [To Test Machine Comprehension, Start by Defining Comprehension](https://mlsanity.com/paper/2005.01525/) (2020)
- [Financial Document Causality Detection Shared Task (FinCausal 2020)](https://mlsanity.com/paper/2012.02505/) (2020)
- [A Survey on Extraction of Causal Relations from Natural Language Text](https://mlsanity.com/paper/2101.06426/) (2021)
- [The Causal News Corpus: Annotating Causal Relations in Event Sentences from News](https://mlsanity.com/paper/2204.11714/) (2022)
- [Improving Event Causality Identification via Self-Supervised Representation Learning on External Causal Statement](https://mlsanity.com/paper/2106.01654/) (2021)
- [KnowDis: Knowledge Enhanced Data Augmentation for Event Causality Detection via Distant Supervision](https://mlsanity.com/paper/2010.10833/) (2020)
- [Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes](https://mlsanity.com/paper/2105.07571/) (2021)
- [Automatic Extraction of Causal Relations from Natural Language Texts: A Comprehensive Survey](https://mlsanity.com/paper/1605.07895/) (2016)
- [LearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identification](https://mlsanity.com/paper/2106.01649/) (2021)
- [Automated Extraction of Socio-political Events from News (AESPEN): Workshop and Shared Task Report](https://mlsanity.com/paper/2005.06070/) (2020)
- [Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2021): Workshop and Shared Task Report](https://mlsanity.com/paper/2108.07865/) (2021)
- [A Study on Agreement in PICO Span Annotations](https://mlsanity.com/paper/1904.09557/) (2019)
- [Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2022): Workshop and Shared Task Report](https://mlsanity.com/paper/2211.11359/) (2022)
- [1Cademy @ Causal News Corpus 2022: Enhance Causal Span Detection via Beam-Search-based Position Selector](https://mlsanity.com/paper/2210.17157/) (2022)
- [1Cademy @ Causal News Corpus 2022: Leveraging Self-Training in Causality Classification of Socio-Political Event Data](https://mlsanity.com/paper/2211.02729/) (2022)
- [IDIAPers @ Causal News Corpus 2022: Extracting Cause-Effect-Signal Triplets via Pre-trained Autoregressive Language Model](https://mlsanity.com/paper/2209.03891/) (2022)
- [Causality Detection using Multiple Annotation Decisions](https://mlsanity.com/paper/2210.14852/) (2022)

## Built on by (most cited first, 4 of 4)

- [BoschAI @ Causal News Corpus 2023: Robust Cause-Effect Span Extraction using Multi-Layer Sequence Tagging and Data Augmentation](https://mlsanity.com/paper/2312.06338/) (2023)
- [Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2023): Workshop and Shared Task Report](https://mlsanity.com/paper/2312.01244/) (2023)
- [WikiCausal: Corpus and Evaluation Framework for Causal Knowledge Graph Construction](https://mlsanity.com/paper/2409.00331/) (2024)
- [Shrome at Touch'e: Soft-Vote Ensembling and Counter-Causal Augmentation for Causality Extraction](https://mlsanity.com/paper/2610.03268/) (2026)

## Abstract (arXiv)

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 contains a causal relation or not. This is a supervised binary classification task. Subtask 2 required participants to identify the Cause, Effect and Signal spans per causal sentence. This could be seen as a supervised sequence labeling task. For both subtasks, participants uploaded their predictions for a held-out test set, and ranking was done based on binary F1 and macro F1 scores for Subtask 1 and 2, respectively. This paper summarizes the work of the 17 teams that submitted their results to our competition and 12 system description papers that were received. The best F1 scores achieved for Subtask 1 and 2 were 86.19% and 54.15%, respectively. All the top-performing approaches involved pre-trained language models fine-tuned to the targeted task. We further discuss these approaches and analyze errors across participants' systems in this paper.