Papers by Yuya Sawada

5 papers
Toward Automatic Delegation Extraction in Japanese Law (2026.eacl-industry)

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Challenge: a higher-level law authorizes a lower-level to implement detailed provisions, which is called delegation.
Approach: They propose a two-stage pipeline system for automatic delegation annotation in Japanese law . they extract keywords that indicate delegation using a named entity recognition approach .
Outcome: The proposed system shows sufficient performance to assist manual annotation in practice.
A Text Embedding Model with Contrastive Example Mining for Point-of-Interest Geocoding (2025.coling-main)

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Challenge: Existing studies have focused on coarse-grained locations, but we focus on fine-grain POIs, which have many candidates with similar names.
Approach: They develop a text embedding-based geocoding model and investigate (1) entry encoding representations and (2) hard negative mining approaches suitable for enhancing the model’s disambiguation ability.
Outcome: The proposed model significantly improves its disambiguation ability and entry encoding representations.
entity-linkings: A Unified Library for Entity Linking (2026.eacl-demo)

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Challenge: Entity linking (EL) is the task of mapping named entities in text to canonical entries in a knowledge base.
Approach: They propose a unified library for using and developing entity linking systems . a strong emphasis is placed on usability, making it highly extensible .
Outcome: a new library aims to disambiguate named entities in text by mapping them to canonical entries in a knowledge base.
JaCorpTrack: Corporate History Event Extraction for Tracking Organizational Changes (2025.emnlp-industry)

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Challenge: Existing information extraction systems are not able to accurately capture organizational changes.
Approach: They propose a task to extract corporate history events related to organizational changes by identifying company names before and after each event, as well as the corresponding date.
Outcome: The proposed task is designed to identify company names before and after an event, as well as the corresponding date.
Coordination Boundary Identification without Labeled Data for Compound Terms Disambiguation (2020.coling-main)

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Challenge: a new method for nominal coordination boundary identification is proposed . it uses pre-trained word embeddings to measure similarities of words and detects the span of coordination .
Approach: They propose a method for nominal coordination boundary identification that uses pre-trained word embeddings to measure similarities of words and detects the span of coordination.
Outcome: The proposed method can identify coordination boundaries without training on labeled data . it is comparable to a recent supervised method for the case when the coordinator conjoins simple noun phrases.

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