Brill, Eric. A report of recent progress in Transformation-based Error-driven Learning. Proceedings of the ARPA Workshop on Human Language Technology.1994.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....in contrast to parsers. An ngram tagger concentrates on the n neighbors of a word (where n tends to be 2 or 3) ignoring the global sentence structure. Also, many part of speech tagging systems are only concerned with resolving ambiguity, not dealing with unknown words. Kupiec [8] and Brill [3] make use of morphology to handle unknown words during part of speech tagging. Brill s tagger begins by tagging unknown words as proper nouns if capitalized, common nouns if not. Then the tagger learns various transformational rules by training on a tagged corpus. It applies these rules to ....

Eric Brill. A report of recent progress in transformation-based error-driven learning. Proeeedings of the Twelfth National Conference on Artifieal rntelli9ence , pages 722-727, 1994.

.... Introduction Eric Brill in his recent thesis (1993b) proposed an approach called transformation based error driven learning that can statistically derive linguistic models from corpora, and he has applied the approach in various domains including part of speech tagging (Brill, 1992; Brill, 1994) and building phrase structure trees (Brill, 1993a) The method learns a sequence of symbolic rules that characterize important contextual factors and use them to predict a most likely value. The search for such factors only requires counting various sets of events that actually occur in a ....

Brill, Eric. 1994. A report of recent progress in transformation-based error-driven learning. In Proceedings of the ARPA Workshop on Human Language Technology, March, 1994.

....of Stuttgart. 1 The 1 Thanks to Uli Heid for making this corpus available to us. texts in that corpus are taken from the Frankfurter Rundschau, a daily newspaper. We split the corpus into a 7=8 training corpus (60 710 tokens) and a 1=8 test corpus (8 887 tokens) using a tool supplied by Eric Brill that divides a corpus sentence by sentence. The test corpus then contains sentences from many different sections of the corpus. The average rate of ambiguity in the test corpus is 1.50. That means that on average for any token in the test corpus there is a choice of 1.5 tags in the lexicon, if ....

Eric Brill. 1994. A report of recent progress in transformation-based error-driven learning. In Proceedings of AAAI.

....to refer both to the part of speech of a word and to the tag that is used to label it. We used two different taggers (on separate copies of each file) in order to compare their results: the POST part of speech tagger (Weischedel, Meteer, Schwartz, Ramshaw, and Palmucci, 1993) and the Brill tagger (Brill, 1992, 1994). Both taggers use the same set of syntactic categories the University of Pennsylvania tag set, but because they use different methods, they might not agree on the appropriate tag for any given word. POST uses a probability model, whereas Brill s tagger uses a learning paradigm called ....

....they use different methods, they might not agree on the appropriate tag for any given word. POST uses a probability model, whereas Brill s tagger uses a learning paradigm called transformation based error driven learning. Despite their different approaches, the two taggers have similar error rates (Brill, 1994). Since neither tagger was retrained on text similar to the writing in the experimental task, it is likely that the error rates in our data are higher than the error rates reported for text similar to the taggers training data. 6.2 Statistical analysis of the data We have now reached the main ....

Brill, Eric (1994). "A report of recent progress in transformation-based error-driven learning." Proceedings of the 12th National Conference on Artificial Intelligence (AAAI-94), Seattle, 722--727.

....in contrast to parsers. An n gram tagger concentrates on the n neighbors of a word (where n tends to be 2 or 3) ignoring the global sentence structure. Also, many part of speech tagging systems are only concerned with resolving ambiguity, not dealing with unknown words. Kupiec [8] and Brill [3] make use of morphology to handle unknown words during part ofspeech tagging. Brill s tagger begins by tagging unknown words as proper nouns if capitalized, common nouns if not. Then the tagger learns various transformational rules by training on a tagged corpus. It applies these rules to unknown ....

Eric Brill. A report of recent progress in transformation-based error-driven learning. Proceedings of the Twelfth National Conference on Artifical Intelligence, pages 722--727, 1994.

....corpus and learns how to deduce the most likely part of speech tag for a word. Once the training is completed, the tagger can be used to annotate new, unannotated corpora based on the tag set of the training corpus. The tagger has been trained for tagging English texts with an accuracy of 97 (Brill, 1994). In this study Brill s rule based part of speech (PoS) tagger is tested on Hungarian. The main goal is i) to find out if Brill s system is immediately applicable to a language, which greatly differs in structure from English, with a high degree of accuracy and (if not) ii) to improve the training ....

Brill, E. 1994. A Report of Recent Progress in Transformation-Based Error-Driven Learning. ARPA-94.

....corpus and learns how to deduce the most likely part of speech tag for a word. Once the training is completed, the tagger can be used to annotate new, unannotated corpora based on the tag set of the training corpus. The tagger has been trained for tagging English texts with an accuracy of 97 (Brill, 1994). In this study Brill s rule based part of speech (PoS) tagger is tested on Hungarian, a dissimilar language, concerning both morphology and syntax, to English. The main goal is i) to find out if Brill s system is immediately applicable to a language, which greatly differs in structure from ....

Brill, E. 1994. A Report of Recent Progress in Transformation-Based Error-Driven Learning. ARPA-94.

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Eric Brill. 1994. A report of recent progress in transformation-based error-driven learning.

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Brill, Eric. A report of recent progress in Transformation-based Error-driven Learning. Proceedings of the ARPA Workshop on Human Language Technology.1994.

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Brill, Eric. A report of recent progress in Transformation-based Error-driven Learning. Proceedings of the ARPA Workshop on Human Language Technology.1994.

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Brill, E. (1994). A report of recent progress in transformation-based error-driven learning.

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Eric Brill. 1994. A report of recent progress in transformation-based error-driven learning.

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Brill, E. (1994). A report of recent progress in transformation-based error-driven learning.

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