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8,808
Unsupervised Part-of-speech Tagging
, 1996
"... Different approaches have been taken in order to solve the part-of-speech tagging problem. Several methods for unsupervised tagging have obtained good accuracies in practice. The approach taken by Brill [Bri95] obtains results comparable to the best existing taggers. In this paper we explore the det ..."
Abstract
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Cited by 1 (0 self)
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Different approaches have been taken in order to solve the part-of-speech tagging problem. Several methods for unsupervised tagging have obtained good accuracies in practice. The approach taken by Brill [Bri95] obtains results comparable to the best existing taggers. In this paper we explore
A Maximum Entropy Model for Part-Of-Speech Tagging
, 1996
"... This paper presents a statistical model which trains from a corpus annotated with Part-OfSpeech tags and assigns them to previously unseen text with state-of-the-art accuracy(96.6%). The model can be classified as a Maximum Entropy model and simultaneously uses many contextual "features" t ..."
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Cited by 580 (1 self)
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This paper presents a statistical model which trains from a corpus annotated with Part-OfSpeech tags and assigns them to previously unseen text with state-of-the-art accuracy(96.6%). The model can be classified as a Maximum Entropy model and simultaneously uses many contextual "
Probabilistic Part-of-Speech Tagging Using Decision Trees
, 1994
"... In this paper, a new probabilistic tagging method is presented which avoids problems that Markov Model based taggers face, when they have to estimate transition probabilities from sparse data. In this tagging method, transition probabilities are estimated using a decision tree. Based on this method, ..."
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Cited by 1058 (9 self)
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, a part-of-speech tagger (called TreeTagger) has been implemented which achieves 96.36 % accuracy on Penn-Treebank data which is better than that of a trigram tagger (96.06 %) on the same data.
Using Grammatical Inference Methods for Automatic Part-of-Speech Tagging
- In LREC'98
, 1998
"... In this paper we present a part-of-speech tagging system based on a structural language model learnt automatically using grammatical inference techniques, in particular the ECGI algorithm. In order to test the capabilities of the proposed approach, we carried out some experiments to evaluate the qua ..."
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Cited by 5 (4 self)
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Tagging Problem: An Overview Part-of-Speech tagging is a well-known disambiguation proble...
Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network
- IN PROCEEDINGS OF HLT-NAACL
, 2003
"... We present a new part-of-speech tagger that demonstrates the following ideas: (i) explicit use of both preceding and following tag contexts via a dependency network representation, (ii) broad use of lexical features, including jointly conditioning on multiple consecutive words, (iii) effective ..."
Abstract
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Cited by 693 (23 self)
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We present a new part-of-speech tagger that demonstrates the following ideas: (i) explicit use of both preceding and following tag contexts via a dependency network representation, (ii) broad use of lexical features, including jointly conditioning on multiple consecutive words, (iii
TnT - A Statistical Part-Of-Speech Tagger
, 2000
"... Trigrams'n'Tags (TnT) is an efficient statistical part-of-speech tagger. Contrary to claims found elsewhere in the literature, we argue that a tagger based on Markov models performs at least as well as other current approaches, including the Maximum Entropy framework. A recent comparison h ..."
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Cited by 540 (5 self)
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Trigrams'n'Tags (TnT) is an efficient statistical part-of-speech tagger. Contrary to claims found elsewhere in the literature, we argue that a tagger based on Markov models performs at least as well as other current approaches, including the Maximum Entropy framework. A recent comparison
Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging
- Computational Linguistics
, 1995
"... this paper, we will describe a simple rule-based approach to automated learning of linguistic knowledge. This approach has been shown for a number of tasks to capture information in a clearer and more direct fashion without a compromise in performance. We present a detailed case study of this learni ..."
Abstract
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Cited by 924 (8 self)
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of this learning method applied to part of speech tagging
A practical part-of-speech tagger
- IN PROCEEDINGS OF THE THIRD CONFERENCE ON APPLIED NATURAL LANGUAGE PROCESSING
, 1992
"... We present an implementation of a part-of-speech tagger based on a hidden Markov model. The methodology enables robust and accurate tagging with few resource requirements. Only a lexicon and some unlabeled training text are required. Accuracy exceeds 96%. We describe implementation strategies and op ..."
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Cited by 409 (5 self)
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We present an implementation of a part-of-speech tagger based on a hidden Markov model. The methodology enables robust and accurate tagging with few resource requirements. Only a lexicon and some unlabeled training text are required. Accuracy exceeds 96%. We describe implementation strategies
A New Approach to the POS Tagging Problem Using Evolutionary Computation
"... The purpose of part-of-speech tagging is to automatically tag the words of a text, written in a certain language, with labels that usually take the form of acronyms that designate the appropriate parts-of-speech. In this paper we propose a new approach to the problem that divides it in two different ..."
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The purpose of part-of-speech tagging is to automatically tag the words of a text, written in a certain language, with labels that usually take the form of acronyms that designate the appropriate parts-of-speech. In this paper we propose a new approach to the problem that divides it in two
Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments
"... We address the problem of part-of-speech tagging for English data from the popular microblogging service Twitter. We develop a tagset, annotate data, develop features, and report tagging results nearing 90 % accuracy. The data and tools have been made available to the research community with the goa ..."
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Cited by 184 (9 self)
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We address the problem of part-of-speech tagging for English data from the popular microblogging service Twitter. We develop a tagset, annotate data, develop features, and report tagging results nearing 90 % accuracy. The data and tools have been made available to the research community
Results 1 - 10
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8,808
