A Statistical Part-of-Speech Tagger for Persian
نویسنده
چکیده
This paper presents the statistical part-ofspeech tagger HunPoS trained on a Persian corpus. The result of the experiments shows that HunPoS provides an overall accuracy of 96.9%, which is the best result reported for Persian part-of-speech tagging.
منابع مشابه
A Persian Part-Of-Speech Tagger Based on Morphological Analysis
This paper describes a method based on morphological analysis of words for a Persian Part-Of-Speech (POS) tagging system. This is a main part of a process for expanding a large Persian corpus called Peyekare (or Textual Corpus of Persian Language). Peykare is arranged into two parts: annotated and unannotated parts. We use the annotated part in order to create an automatic morphological analyze...
متن کاملStudying impressive parameters on the performance of Persian probabilistic context free grammar parser
In linguistics, a tree bank is a parsed text corpus that annotates syntactic or semantic sentence structure. The exploitation of tree bank data has been important ever since the first large-scale tree bank, The Penn Treebank, was published. However, although originating in computational linguistics, the value of tree bank is becoming more widely appreciated in linguistics research as a whole. F...
متن کاملA Probabilistic Approach to Persian Ezafe Recognition
In this paper, we investigate the problem of Ezafe recognition in Persian language. Ezafe is an unstressed vowel that is usually not written, but is intelligently recognized and pronounced by human. Ezafe marker can be placed into noun phrases, adjective phrases and some prepositional phrases linking the head and modifiers. Ezafe recognition in Persian is indeed a homograph disambiguation probl...
متن کاملUse of linguistic features for improving English-Persian SMT
In this paper, we investigate the effects of using linguistic information for improvement of statistical machine translation for English-Persian language pair. We choose POS tags as helping linguistic feature. A monolingual Persian corpus with POS tags is prepared and variety of tags is chosen to be small. Using the POS tagger trained on this corpus, we apply a factored translation model. We al...
متن کاملDeveloping a Persian Part of Speech Tagger
Assigning grammatical categories to words in a text is an important component of a natural language processing (NLP) system. Corpora tagged with Part of speech (POS) information are often used as a prerequisite for more complex NLP applications such as information extraction, syntactic parsing, machine translation or semantic field annotation. They are also used to help train statistical models...
متن کامل