NER Model for Legal Texts Released in January 2024, this is a Turkish BERT language model pretrained from scratch on an optimized BERT architecture using a 2 GB Turkish legal corpus. The corpus was sourced from legal related thesis documents available in the Higher Education Board National Thesis Center (YÖKTEZ). The model has been fine tuned for Named Entity Recognition (NER) tasks on human annotated datasets provided by NewMind , a legal tech company in Istanbul, Turkey. In our paper, we outline the steps taken to train this model and demonstrate its superior performance compared to previous approaches. Overview Preprint Paper : https://arxiv.org/abs/2407.00648 Architecture : Optimized BERT Base Language : Turkish Supported Labels : Person Law Publication Government Corporation Other Project Money Date Location Court Model Name : LegalTurk Optimized BERT How to Use Use a pipeline as a high level helper Load model directly Authors Farnaz Zeidi, Mehmet Fatih Amasyali, Çigdem Erol License This model is shared under the CC BY NC SA 4.0 License. You are free to use, share, and adapt the model for non commercial purposes, provided that you give appropriate credit to the authors. For co…
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