Data Processing and Annotation Schemes for FinCausal Shared Task
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Abstract (arXiv)
This document explains the annotation schemes used to label the data for the FinCausal Shared Task (Mariko et al., 2020). This task is associated to the Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation (FNP-FNS 2020), to be held at The 28th International Conference on Computational Linguistics (COLING'2020), on December 12, 2020.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Dec 2020.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1.
3 papers.
- 2022Towards Fine-grained Causal Reasoning and QAcited by 13
- 2023EDeR: A Dataset for Exploring Dependency Relations Between Eventscited by 0
- 2024Increasing the Accessibility of Causal Domain Knowledge via Causal Information Extraction Methods: A Case Study in the Semiconductor Manufacturing Industrycited by 0
- 2024Increasing the Accessibility of Causal Domain Knowledge via Causal Information Extraction Methods: A Case Study in the Semiconductor Manufacturing Industry15 Nov 2024
- 2023EDeR: A Dataset for Exploring Dependency Relations Between Events4 Apr 2023
- 2022Towards Fine-grained Causal Reasoning and QA15 Apr 2022