While making investment decisions by reading financial documents, investors need to differentiate between in-claim and outof-claim numerals. In this paper, we present a tool which does it automatically. It extracts context embeddings of the numerals using one of the transformer based pre-trained language model called BERT. After this, it uses a Logistic Regression based model to detect whether the numerals is in-claim or out-of-claim. We use FinNum-3 (English) dataset to train our model. After conducting rigorous experiments we achieve a Macro F1 score of 0.8223 on the validation set. We have open-sourced this tool and it can be accessed from https://github.com/sohomghosh/FiNCAT_Financial_Numeral_Claim_Analysis_Tool
FiNCAT: Financial Numeral Claim Analysis Tool
A tool utilizing BERT for context embedding and Logistic Regression for classification is presented to automatically differentiate between in-claim and out-of-claim numerals in financial documents.
- Year
- 2022
- Venue
- arXiv 2022
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- 2
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- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2202.00631ARXIV-DEFAULT
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