Phrase-Based Statistical Model for Korean Morpheme Segmentation and POS Tagging
نویسندگان
چکیده
منابع مشابه
Generalized unknown morpheme guessing for hybrid POS tagging of Korean
Most of errors in Korean morphological analysis and POS (Part-of-Speech) tagging are caused by unknown morphemes. This paper presents a generalized unknown morpheme handling method with P OSTAG (POStech TAGger) which is a statistical/rule based hybrid POS tagging system. The generalized unknown morpheme guessing is based on a combination of a morpheme pattern dictionary which encodes general le...
متن کاملSyllable-Pattern-Based Unknown-Morpheme Segmentation and Estimation for Hybrid Part-of-Speech Tagging of Korean
Most errors in Korean morphological analysis and part-of-speech (POS) tagging are caused by unknown morphemes. This paper presents a syllable-pattern-based generalized unknownmorpheme-estimation method with POSTAG (POStech TAGger), which is a statistical and rule-based hybrid POS tagging system. This method of guessing unknown morphemes is based on a combination of a morpheme pattern dictionary...
متن کاملAn improved joint model: POS tagging and dependency parsing
Dependency parsing is a way of syntactic parsing and a natural language that automatically analyzes the dependency structure of sentences, and the input for each sentence creates a dependency graph. Part-Of-Speech (POS) tagging is a prerequisite for dependency parsing. Generally, dependency parsers do the POS tagging task along with dependency parsing in a pipeline mode. Unfortunately, in pipel...
متن کاملA Transition-based Model for Joint Segmentation, POS-tagging and Normalization
We propose a transition-based model for joint word segmentation, POS tagging and text normalization. Different from previous methods, the model can be trained on standard text corpora, overcoming the lack of annotated microblog corpora. To evaluate our model, we develop an annotated corpus based on microblogs. Experimental results show that our joint model can help improve the performance of wo...
متن کاملCRF-based Hybrid Model for Word Segmentation, NER and even POS Tagging
This paper presents systems submitted to the close track of Fourth SIGHAN Bakeoff. We built up three systems based on Conditional Random Field for Chinese Word Segmentation, Named Entity Recognition and Part-Of-Speech Tagging respectively. Our systems employed basic features as well as a large number of linguistic features. For segmentation task, we adjusted the BIO tags according to confidence...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEICE Transactions on Information and Systems
سال: 2018
ISSN: 0916-8532,1745-1361
DOI: 10.1587/transinf.2017edp7085