Kenzo Kurotsuchi


2017

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StruAP: A Tool for Bundling Linguistic Trees through Structure-based Abstract Pattern
Kohsuke Yanai | Misa Sato | Toshihiko Yanase | Kenzo Kurotsuchi | Yuta Koreeda | Yoshiki Niwa
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

We present a tool for developing tree structure patterns that makes it easy to define the relations among textual phrases and create a search index for these newly defined relations. By using the proposed tool, users develop tree structure patterns through abstracting syntax trees. The tool features (1) intuitive pattern syntax, (2) unique functions such as recursive call of patterns and use of lexicon dictionaries, and (3) whole workflow support for relation development and validation. We report the current implementation of the tool and its effectiveness.

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bunji at SemEval-2017 Task 3: Combination of Neural Similarity Features and Comment Plausibility Features
Yuta Koreeda | Takuya Hashito | Yoshiki Niwa | Misa Sato | Toshihiko Yanase | Kenzo Kurotsuchi | Kohsuke Yanai
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

This paper describes a text-ranking system developed by bunji team in SemEval-2017 Task 3: Community Question Answering, Subtask A and C. The goal of the task is to re-rank the comments in a question-and-answer forum such that useful comments for answering the question are ranked high. We proposed a method that combines neural similarity features and hand-crafted comment plausibility features, and we modeled inter-comments relationship using conditional random field. Our approach obtained the fifth place in the Subtask A and the second place in the Subtask C.