Ken Yano


2023

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DISTANT: Distantly Supervised Entity Span Detection and Classification
Ken Yano | Makoto Miwa | Sophia Ananiadou
The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks

We propose a distantly supervised pipeline NER which executes entity span detection and entity classification in sequence named DISTANT (DIstantly Supervised enTity spAN deTection and classification).The former entity span detector extracts possible entity mention spans by the distant supervision. Then the later entity classifier assigns each entity span to one of the positive entity types or none by employing a positive and unlabeled (PU) learning framework. Two models were built based on the pre-trained SciBERT model and fine-tuned with the silver corpus generated by the distant supervision. Experimental results on BC5CDR and NCBI-Disease datasets show that our method outperforms the end-to-end NER baselines without PU learning by a large margin. In particular, it increases the recall score effectively.

2021

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Pipeline Signed Japanese Translation Focusing on a Post-positional Particle Complement and Conjugation in a Low-resource Setting
Ken Yano | Akira Utsumi
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021