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Trigram tagger

In computational linguistics, a trigram tagger is a statistical method for automatically identifying words as being nouns, verbs, adjectives, adverbs… 
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Related topics

Related topics

7 relations
BigramComputational linguisticsMarkov modelN-gram

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2014
2014
Tagging Complex Non-Verbal German Chunks with Conditional Random Fields
We report on chunk tagging methods for German that recognize complex non-verbal phrases using structural chunk tags with… 
2012
2012
Boosting statistical tagger accuracy with simple rule-based grammars
We report on several experiments on combining a rule-based tagger and a trigram tagger for Spanish. The results show that one can… 
2011
2011
Projecting Farsi POS Data To Tag Pashto
We present our findings on projecting part of speech (POS) information from a well resourced language, Farsi, to help tag a lower… 
2010
2010
The Design of a Proofreading Software Service
Web applications have the opportunity to check spelling, style, and grammar using a software service architecture. A software… 
2008
2008
Investigating language independence in HMM PoS/MSD-tagging
The paper presents an investigation of functional dependencies in morphosyntactic tagging using hidden Markov models. Starting… 
2006
2006
Evaluating Morphosyntactic Tagging of Croatian Texts
This paper describes results of the first successful effort in applying a stochastic strategy – or, namely, a second order Markov… 
2006
2006
Generating an Unknown Word Tagger for Dutch using automatically learned Affix-rules
In this paper I will describe the problem of Unknown Word Tagging for the Dutch language. I will also explain how I have adapted… 
2005
2005
Unigram Backoff vs . TnT Evaluating Part of Speech Taggers Introduction to Computational Linguistics
Automated statistical part-of-speech (POS) tagging has been a very active research area for many years and is the foundation of… 
2002
2002
Beyond Tag Trigrams: New Local Features for Tagging
The set of features used by any predictive model is of pivotal importance to its performance. In this paper we show the utility… 
1997
1997
Using Multiple Taggers to Improve English Part-of-speech Tagging by Error Learning
Many approaches to Part-of-Speech tagging have reached accuracy about 96-97% which is close to the upper bound, and little… 
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