Labelling factual information in legal cases using fine-tuned BERT models
Labelling factual information on the token level in legal cases requires legal expertise and is time-consuming. This thesis proposes transfer-learning and fine-tuning implementation of pre-trained state-of-the-art BERT models to perform this labelling task. Investigations are done to compare whether...
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| Format: | Others |
| Language: | English |
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Uppsala universitet, Statistiska institutionen
2021
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-447230 |
