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CADEL: A Corpus of Administrative Web Documents for Japanese Entity Linking

arXiv 2603.29336 ↗First posted 31 Mar 2026cs.CLcited by 0

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Abstract (arXiv)

Entity linking is the task of associating linguistic expressions with entries in a knowledge base that represent real-world entities and concepts. Language resources for this task have primarily been developed for English, and the resources available for evaluating Japanese systems remain limited. In this study, we develop a corpus design policy for the entity linking task and construct an annotated corpus for training and evaluating Japanese entity linking systems, with rich coverage of linguistic expressions referring to entities that are specific to Japan. Evaluation of inter-annotator agreement confirms the high consistency of the annotations in the corpus, and a preliminary experiment on entity disambiguation based on string matching suggests that the corpus contains a substantial number of non-trivial cases, supporting its potential usefulness as an evaluation benchmark.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 42 references that are in the map. First posted on arXiv 31 Mar 2026.

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References · 6

  1. 2020A Survey of Knowledge-Enhanced Text Generationcited by 120
  2. 2022Revisiting DocRED -- Addressing the False Negative Problem in Relation Extractioncited by 57
  3. 2020Entity Linking in 100 Languagescited by 52
  4. 2021Robustness Evaluation of Entity Disambiguation Using Prior Probes:the Case of Entity Overshadowingcited by 11
  5. 2023A Fair and In-Depth Evaluation of Existing End-to-End Entity Linking Systemscited by 2
  6. 2023DaMuEL: A Large Multilingual Dataset for Entity Linkingcited by 2

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