UD_Japanese-CEJC: Dependency Relation Annotation on Corpus of Everyday Japanese Conversation

Conference name: the 24th Meeting of the Special Interest Group on Discourse and Dialogue, Conference place: Prague, Czechia, Session period: 2023/09/11-15, Organizer: Association for Computational Linguisticsapplication/pdfNational Institute for Japanese Language and LinguisticsTohoku UniversityMegagon Labs, Tokyo, Recruit Co., LtdNational Institute for Japanese Language and LinguisticsIn this study, we have developed Universal Dependencies (UD) resources for spoken Japanese in the Corpus of Everyday Japanese Conversation (CEJC). The CEJC is a large corpus of spoken language that encompasses various everyday conversations in Japanese, and includes word delimitation and part-of-speech annotation. We have newly annotated Long Word Unit delimitation and Bunsetsu (Japanese phrase)-based dependencies, including Bunsetsu boundaries, for CEJC. The UD of Japanese resources was constructed in accordance with hand-maintained conversion rules from the CEJC with two types of word delimitation, part-of-speech tags and Bunsetsu-based syntactic dependency relations. Furthermore, we examined various issues pertaining to the construction of UD in the CEJC by comparing it with the written Japanese corpus and evaluating UD parsing accuracy.conference pape

Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP

Transfer learning, particularly approaches that combine multi-task learning with pre-trained contextualized embeddings and fine-tuning, have advanced the field of Natural Language Processing tremendously in recent years. In this paper we present MaChAmp, a toolkit for easy fine-tuning of contextualized embeddings in multi-task settings. The benefits of MaChAmp are its flexible configuration options, and the support of a variety of natural language processing tasks in a uniform toolkit, from text classification and sequence labeling to dependency parsing, masked language modeling, and text generation.Comment: https://machamp-nlp.github.io

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Proceedings of the Fifth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2018)

Peer reviewe

Development of Linguistic Linked Open Data Resources for Collaborative Data-Intensive Research in the Language Sciences

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