Taishi Chika


2024

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Domain Transferable Semantic Frames for Expert Interview Dialogues
Taishi Chika | Taro Okahisa | Takashi Kodama | Yin Jou Huang | Yugo Murawaki | Sadao Kurohashi
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

Interviews are an effective method to elicit critical skills to perform particular processes in various domains. In order to understand the knowledge structure of these domain-specific processes, we consider semantic role and predicate annotation based on Frame Semantics. We introduce a dataset of interview dialogues with experts in the culinary and gardening domains, each annotated with semantic frames. This dataset consists of (1) 308 interview dialogues related to the culinary domain, originally assembled by Okahisa et al. (2022), and (2) 100 interview dialogues associated with the gardening domain, which we newly acquired. The labeling specifications take into account the domain-transferability by adopting domain-agnostic labels for frame elements. In addition, we conducted domain transfer experiments from the culinary domain to the gardening domain to examine the domain transferability with our dataset. The experimental results showed the effectiveness of our domain-agnostic labeling scheme.

2023

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Toward a corpus-based identification of nominal relationality and uniqueness: A constructionist approach
Kazuho Kambara | Taishi Chika
Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation