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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2310.19055 |
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| _version_ | 1866914729994223616 |
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| author | Alqaaidi, Sakher Khalil Bozorgi, Elika Shams, Afsaneh Kochut, Krzysztof |
| author_facet | Alqaaidi, Sakher Khalil Bozorgi, Elika Shams, Afsaneh Kochut, Krzysztof |
| contents | Named Entity Recognition (NER) and Relation Classification (RC) are important steps in extracting information from unstructured text and formatting it into a machine-readable format. We present a survey of recent deep learning models that address named entity recognition and relation classification, with focus on few-shot learning performance. Our survey is helpful for researchers in knowing the recent techniques in text mining and extracting structured information from raw text. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_19055 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | A Few-Shot Learning Focused Survey on Recent Named Entity Recognition and Relation Classification Methods Alqaaidi, Sakher Khalil Bozorgi, Elika Shams, Afsaneh Kochut, Krzysztof Computation and Language Named Entity Recognition (NER) and Relation Classification (RC) are important steps in extracting information from unstructured text and formatting it into a machine-readable format. We present a survey of recent deep learning models that address named entity recognition and relation classification, with focus on few-shot learning performance. Our survey is helpful for researchers in knowing the recent techniques in text mining and extracting structured information from raw text. |
| title | A Few-Shot Learning Focused Survey on Recent Named Entity Recognition and Relation Classification Methods |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2310.19055 |