arXiv 2410.011002025-04-02cs.CL

解锁韩语动词：面向动词词典的用户友好探索

Unlocking Korean Verbs: A User-Friendly Exploration into the Verb Lexicon

Seoultech（首尔科技大学）；The University of British Columbia（不列颠哥伦比亚大学）；The Chinese University of Hong Kong（香港中文大学）；dot Inc.（42dot公司）；Seoul National University（首尔大学）；National Institute of Korean Language（韩国国立国语院）；KAIST（韩国科学技术院）；Anyang University（安阳大学）

Seohyun Song, Eunkyul Leah Jo, Yige Chen, Jeen-Pyo Hong, Kyuwon Kim, Jin Wee, Miyoung Kang, KyungTae Lim, Jungyeul Park, Chulwoo Park

备注：: NAACL 2025 System Demonstrations

阅读 PDF

arXiv 页面 ↗HTML 原文 ↗

AI总结：

本文介绍了一个用户友好的Web界面和Python库，用于收集整合韩语动词相关信息（如次范畴框架）并简化句法分析与语义角色标注，助力基于Sejong词典数据集的韩语处理应用开发。

摘要：

Sejong词典数据集提供了一项宝贵的资源，涵盖了形态学、句法和语义表示的广泛覆盖。该数据集可用于更层次探索语言信息。该数据集中标注的语言语言结构构成了揭示词与短语之间关系及其与目标动词关联的基础。本文介绍了一个用户友好的Web界面，旨在收集和整合动词相关信息，特别关注次范畴框架。此外，本文概述了通过将次范畴框架与相应例句对齐来映射这些信息的努力。进一步地，我们提供了一个Python库，以简化句法分析和语义角色标注。这些工具旨在帮助有兴趣利用Sejong词典数据集开发韩语处理应用的个人。

英文摘要：

The Sejong dictionary dataset offers a valuable resource, providing extensive coverage of morphology, syntax, and semantic representation. This dataset can be utilized to explore linguistic information in greater depth. The labeled linguistic structures within this dataset form the basis for uncovering relationships between words and phrases and their associations with target verbs. This paper introduces a user-friendly web interface designed for the collection and consolidation of verb-related information, with a particular focus on subcategorization frames. Additionally, it outlines our efforts in mapping this information by aligning subcategorization frames with corresponding illustrative sentence examples. Furthermore, we provide a Python library that would simplify syntactic parsing and semantic role labeling. These tools are intended to assist individuals interested in harnessing the Sejong dictionary dataset to develop applications for Korean language processing.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。