CLDec 4, 2020
Data Processing and Annotation Schemes for FinCausal Shared Task
arXiv:2012.02498v110 citations
Originality Synthesis-oriented
AI Analysis
This work provides data annotation guidelines for researchers working on causal relation extraction in the financial domain, which is an incremental contribution.
This paper describes the annotation schemes developed for the FinCausal Shared Task, which focuses on identifying causal relations in financial texts. The task is part of the FNP-FNS 2020 workshop at COLING'2020.
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.