Enhancing Language Models for Financial Relation Extraction with Named Entities and Part-of-Speech
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866910442622812160 |
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| author | Li, Menglin Lim, Kwan Hui |
| author_facet | Li, Menglin Lim, Kwan Hui |
| contents | The Financial Relation Extraction (FinRE) task involves identifying the entities and their relation, given a piece of financial statement/text. To solve this FinRE problem, we propose a simple but effective strategy that improves the performance of pre-trained language models by augmenting them with Named Entity Recognition (NER) and Part-Of-Speech (POS), as well as different approaches to combine these information. Experiments on a financial relations dataset show promising results and highlights the benefits of incorporating NER and POS in existing models. Our dataset and codes are available at https://github.com/kwanhui/FinRelExtract. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_06665 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Enhancing Language Models for Financial Relation Extraction with Named Entities and Part-of-Speech Li, Menglin Lim, Kwan Hui Computation and Language Information Retrieval Machine Learning The Financial Relation Extraction (FinRE) task involves identifying the entities and their relation, given a piece of financial statement/text. To solve this FinRE problem, we propose a simple but effective strategy that improves the performance of pre-trained language models by augmenting them with Named Entity Recognition (NER) and Part-Of-Speech (POS), as well as different approaches to combine these information. Experiments on a financial relations dataset show promising results and highlights the benefits of incorporating NER and POS in existing models. Our dataset and codes are available at https://github.com/kwanhui/FinRelExtract. |
| title | Enhancing Language Models for Financial Relation Extraction with Named Entities and Part-of-Speech |
| topic | Computation and Language Information Retrieval Machine Learning |
| url | https://arxiv.org/abs/2405.06665 |