Ponrawee Prasertsom, Apiwat Jaroonpol, Attapol T. Rutherford
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引用次数: 0
摘要
摘要 语篇分析是自然语言处理中一个非常适用的领域。在英语和其他语言中,基于语篇的任务资源非常广泛。然而,泰语迄今为止还缺乏此类资源。我们介绍了泰语话语树库,这是第一个按照宾夕法尼亚大学话语树库风格注释的大型泰语语料库。该语料库包含 10,000 多个句子和 33 种不同关系中的 18,000 个连接词实例。我们在发布该语料库的同时,还发布了我们的 148 个潜在多义话语连接词(共 340 个形义对)列表及其分类标准,以促进未来的研究。我们还开发了用于连接词识别和分类任务的模型。我们的最佳模型在识别任务中的 F1 为 0.96,在意义分类任务中的 F1 为 0.46。我们的结果可作为未来泰语话语任务模型的基准。
The Thai Discourse Treebank: Annotating and Classifying Thai Discourse Connectives
Abstract Discourse analysis is a highly applicable area of natural language processing. In English and other languages, resources for discourse-based tasks are widely available. Thai, however, has hitherto lacked such resources. We present the Thai Discourse Treebank, the first, large Thai corpus annotated in the style of the Penn Discourse Treebank. The resulting corpus has over 10,000 sentences and 18,000 instances of connectives in 33 different relations. We release the corpus alongside our list of 148 potentially polysemous discourse connectives with a total of 340 form-sense pairs and their classification criteria to facilitate future research. We also develop models for connective identification and classification tasks. Our best models achieve an F1 of 0.96 in the identification task and 0.46 on the sense classification task. Our results serve as benchmarks for future models for Thai discourse tasks.
期刊介绍:
The highly regarded quarterly journal Computational Linguistics has a companion journal called Transactions of the Association for Computational Linguistics. This open access journal publishes articles in all areas of natural language processing and is an important resource for academic and industry computational linguists, natural language processing experts, artificial intelligence and machine learning investigators, cognitive scientists, speech specialists, as well as linguists and philosophers. The journal disseminates work of vital relevance to these professionals on an annual basis.