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Equations for Part-of-Speech Tagging
- In Proceedings of the Eleventh National Conference on Artificial Intelligence
, 1993
"... We derive from first principles the basic equations for a few of the basic hidden-Markov-model word taggers as well as equations for other models which may be novel (the descriptions in previous papers being too spare to be sure). We give performance results for all of the models. The results from o ..."
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Cited by 129 (2 self)
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the equations for a variety of models may be derived and thus encourage future authors to give the equations for their model and the derivations thereof. Introduction The last few years have seen a fair number of papers on part-of-speech tagging --- assigning the correct part of speech to each word in a text
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 ..."
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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
Iterative Part-of-Speech Tagging
, 1999
"... . Assigning a category to a given word (tagging) depends on the particular word and on the categories (tags) of neighboring words. A theory that is able to assign tags to a given text is then a recursive logic program by nature. This article describes how iterative induction, a technique that has be ..."
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been proven powerful in the synthesis of recursive logic programs, has been applied to the task of part-of-speech tagging. The main strategy consists of inducing a succession T 1 , T 2 , ..., T n of theories, using in the induction of theory T all the previously induced theories. Each theory
Distributional Part-of-Speech Tagging
- In Proc. of 7th Conference of the European Chapter of the Association for Computational Linguistics
, 1995
"... This paper presents an algorithm for tagging words whose part-of-speech properties are unknown. Unlike previous work, the algorithm categorizes word tokens in context instead of word types. The algorithm is evaluated on the Brown Corpus. ..."
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Cited by 114 (8 self)
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This paper presents an algorithm for tagging words whose part-of-speech properties are unknown. Unlike previous work, the algorithm categorizes word tokens in context instead of word types. The algorithm is evaluated on the Brown Corpus.
Internal and External Tagsets in Part-of-Speech Tagging
- In Proceedings of Eurospeech
, 1997
"... We present an approach to statistical partof -speech tagging that uses two different tagsets, one for its internal and one for its external representation. The internal tagset is used in the underlying Markov model, while the external tagset constitutes the output of the tagger. The internal t ..."
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Cited by 11 (1 self)
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tagset can be modified and optimized to increase tagging accuracy (with respect to the external tagset). We evaluate this approach in an experiment and show that it performs significantly better than approaches using only one tagset. 1 Introduction The task of part-of-speech tagging is to assign
Part-of-Speech Tagging Using the Brill Method
, 2004
"... Part-of-speech tagging is the process of associating each word in a text with it's part-of-speech category and possibly a set of morphosyntactic features. This information is represented by part-of-speech tags. This paper describes an implementation of a part-of-speech tagger for Swedish based ..."
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Part-of-speech tagging is the process of associating each word in a text with it's part-of-speech category and possibly a set of morphosyntactic features. This information is represented by part-of-speech tags. This paper describes an implementation of a part-of-speech tagger for Swedish based
Part-of-Speech Tagging with Neural Networks
, 1994
"... Text corpora which are tagged with part-o[-speech information are useful in many areas of linguistic research. In this paper, a new part-of-speech tagging method based on neural networks (Net-7h.qger) is presented and its performance is compared to that of a 11IvlM-tagger (Cutting ct al., 1992) anti ..."
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Cited by 80 (2 self)
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Text corpora which are tagged with part-o[-speech information are useful in many areas of linguistic research. In this paper, a new part-of-speech tagging method based on neural networks (Net-7h.qger) is presented and its performance is compared to that of a 11IvlM-tagger (Cutting ct al., 1992
Part-of-speech tagging for Swedish
- Department of Linguistics, Uppsala University
, 1999
"... This paper describes the work with a part-of-speech tagger for Swedish. The tagger used in the work was originally designed by Brill (1992) and may be adapted to different languages using annotated training corpora. The training corpus in this case is very small and may be the reason why the tagger ..."
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Cited by 1 (0 self)
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This paper describes the work with a part-of-speech tagger for Swedish. The tagger used in the work was originally designed by Brill (1992) and may be adapted to different languages using annotated training corpora. The training corpus in this case is very small and may be the reason why the tagger
Shallow Parsing as Part-of-Speech Tagging
, 2000
"... Treating shallow parsing as part-of-speech tagging yields results comparable with other, more elaborate approaches. Using the CoNLL 2000 training and testing material, our best model had an accuracy of 94.88%, with an overall FB1 score of 91.94%. The individual FB1 scores for NPs were 92.19%, VPs 92 ..."
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Cited by 10 (0 self)
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Treating shallow parsing as part-of-speech tagging yields results comparable with other, more elaborate approaches. Using the CoNLL 2000 training and testing material, our best model had an accuracy of 94.88%, with an overall FB1 score of 91.94%. The individual FB1 scores for NPs were 92.19%, VPs
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 "
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