Addressing Annotated Data Scarcity in Legal Information Extraction
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-3076-6_6
Reference22 articles.
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2. Mandal, A., Ghosh, K., Ghosh, S., Mandal, S.: A sequence labeling model for catchphrase identification from legal case documents. Artif. Intell. Law 30, 325–358 (2021). https://doi.org/10.1007/s10506-021-09296-2
3. Çetindağ, C., Yazıcıoğlu, B., Koç, A.: Named-entity recognition in Turkish legal texts. Nat. Lang. Eng. 29(3), 615–642 (2023)
4. Darji, H., Mitrović, J., Granitzer, M.: German BERT model for legal named entity recognition. In: 15th International Conference on Agents and Artificial Intelligence, ICAART 2023, Lisbon, Portugal, vol. 3, pp. 723–728 (2023)
5. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);K Satoh,2011
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