Bengali noun phrase chunking based on conditional random fields

K. Sarkar, V. Gayen
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引用次数: 5

Abstract

Noun phrase (NP) chunking deals with extracting the noun phrases from a sentence. While NP chunking is much simpler than parsing, it is still a challenging task to build an accurate and efficient NP chunker. Noun phrase chunking is an important and useful task in many natural language processing applications. It is studied well for English, however not much work has been done for Bengali. This paper presents a Bengali noun phrase chunking approach based on conditional random fields (CRFs) models. Our developed NP chunker has been tested on the ICON 2013 dataset and achieves an impressive F-score of 95.92.
基于条件随机场的孟加拉语名词短语组块
名词短语(NP)组块处理从句子中提取名词短语的问题。虽然NP分块比解析简单得多,但构建准确高效的NP分块器仍然是一项具有挑战性的任务。名词短语组块在许多自然语言处理应用中是一项重要而有用的任务。英语学得很好,但孟加拉语学得不多。提出了一种基于条件随机场(CRFs)模型的孟加拉语名词短语分块方法。我们开发的NP分块器已经在ICON 2013数据集上进行了测试,并取得了令人印象深刻的95.92的f分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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