Rule Based Approach for Arabic Part of Speech Tagging and Name Entity Recognition

Mohammad Hjouj,Isa Olab,Abdulsalam Alarabeyyat

doi:10.14569/ijacsa.2016.070642

Abstract

The aim of this study is to build a tool for Part of Speech (POS) tagging and Name Entity Recognition for Arabic Language, the approach used to build this tool is a rule base technique. The POS Tagger contains two phases:The first phase is to pass word into a lexicon phase, the second level is the morphological phase, and the tagset are (Noun, Verb and Determine). The Named-Entity detector will apply rules on the text and give the correct Labels for each word, the labels are Person(PERS), Location (LOC) and Organization (ORG)

Highlights

Natural Language Processing (NLP) is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human languages
1) Part of speech Part of speech tagging (POST) is known as POS tagging, word classes, morphological classes,lexical tags or just tagging as a process that aims to assign a specific tag to each word of a sentence to indicate the function of that word in a specific context,the suitable tag is chosen from a set of tags based on some rules, examples of part of speech are: nouns,verbs, pronouns, prepositions,adverbs and other tags, the results of part of speech are for many applications such as speech recognition, natural language parsing,information retrieval, information extraction, question answering, text tospeech conversion, machine translation, grammar correction and many more [2]
First the POS tagger was tested on a file that contains 793 word; the result shows that the tagger successfully tagged 679 words

Summary

Introduction

Natural Language Processing (NLP) is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human (natural) languages. 1) Part of speech Part of speech tagging (POST) is known as POS tagging, word classes, morphological classes,lexical tags or just tagging as a process that aims to assign a specific tag to each word of a sentence to indicate the function of that word in a specific context ,the suitable tag is chosen from a set of tags based on some rules, examples of part of speech are: nouns ,verbs, pronouns, prepositions ,adverbs and other tags, the results of part of speech are for many applications such as speech recognition, natural language parsing,information retrieval, information extraction, question answering, text tospeech conversion, machine translation, grammar correction and many more [2]. POS tagging is necessary in many fields such as: text phrase, syntax, semantic analysis and translation [3]

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Results

Conclusion