Data Processing and Annotation Schemes for FinCausal Shared Task
Dominique Mariko, Estelle Labidurie, Yagmur Ozturk, Hanna Abi Akl,, Hugues de Mazancourt
TL;DR
This paper details the annotation schemes developed for the FinCausal Shared Task, aimed at advancing financial narrative processing and summarization at COLING 2020.
Contribution
It introduces specific annotation schemes for labeling data in the FinCausal Shared Task, facilitating research in financial text analysis.
Findings
Annotation schemes enable consistent data labeling.
Supports financial narrative processing research.
Enhances data quality for shared tasks.
Abstract
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.
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Taxonomy
TopicsNatural Language Processing Techniques · Topic Modeling · Semantic Web and Ontologies