Part of Speech Tagging in Manipuri: A Rule based Approach

The Computational Complexity of Rule-Based Part-of-Speech Tagging

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

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...

Combining Rule-Based and Case-Based Learning for Iterative Part-of-Speech Tagging

In this article we show how the accuracy of a rule based first order theory may be increased by combining it with a case-based approach in a classification task. Case-based learning is used when the rule language bias is exhausted. This is achieved in an iterative approach. In each iteration theories consisting of first order rules are induced and covered examples are removed. The process stops...

A Neural Network Approach to Part-of-Speech Tagging*

Neural networks are one of the most efficient techniques for learning from scarce data. This property is very useful when trying to build a part-of-speech tagger. Available part-of-speech taggers need huge amounts of hand tagged text, but for Portuguese there is no such corpora available. In this paper we propose a neural network that, apparently, is capable of overcoming the huge training corp...

A Hybrid Approach to Part-of-Speech Tagging

Part-of-Speech (PoS) Tagging – the automatic annotation of lexical categories – is a widely used early stage of linguistic text analysis. One approach, rule-based morphological anaylsis, employs linguistic knowledge in the form of hand-coded rules to derive a set of possible analyses for each input token, but is known to produce highly ambiguous results. Stochastic tagging techniques such as Hi...