@inproceedings{2a775b2080824a7c88bee948ec29b6e3,
title = "Tibetan syllable-based functional chunk boundary identification",
abstract = "Tibetan syntactic functional chunk parsing is aimed at identifying syntactic constituents of Tibetan sentences. In this paper, based on the Tibetan syntactic functional chunk description system, we propose a method which puts syllables in groups instead of word segmentation and tagging and use the Conditional Random Fields (CRFs) to identify the functional chunk boundary of a sentence. According to the actual characteristics of the Tibetan language, we firstly identify and extract the syntactic markers as identification characteristics of syntactic functional chunk boundary in the text preprocessing stage, while the syntactic markers are composed of the sticky written form and the non-sticky written form. Afterwards we identify the syntactic functional chunk boundary using CRF. Experiments have been performed on a Tibetan language corpus containing 46783 syllables and the precision, recall rate and F value respectively achieves 75.70\%, 82.54\% and 79.12\%. The experiment results show that the proposed method is effective when applied to a small-scale unlabeled corpus and can provide foundational support for many natural language processing applications such as machine translation.",
keywords = "CRF, Chunk boundary recognition, Syllable, Syntactic marker, Tibetan syntactic functional chunk",
author = "Shumin Shi and Yujian Liu and Tianhang Wang and Congjun Long and Heyan Huang",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 16th China National Conference on Computational Linguistics, CCL 2017 and 5th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2017 ; Conference date: 13-10-2017 Through 15-10-2017",
year = "2017",
doi = "10.1007/978-3-319-69005-6\_36",
language = "English",
isbn = "9783319690049",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "439--448",
editor = "Maosong Sun and Baobao Chang and Xiaojie Wang and Deyi Xiong",
booktitle = "Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data - 16th China National Conference, CCL 2017 and 5th International Symposium, NLP-NABD 2017, Proceedings",
address = "Germany",
}