E. Brill. A simple rule-based part-of-speech tagger. In Proceedings of ANLP-92, 3rd Conference on Applied Natural Language Processing, pages 152--155, Trento, IT, 1992. Home/Search Document Details and Download
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Dimensional Representations of Knowledge in Online Community - Mcarthur, Bruza (Correct)
....from utterances. The technology has matured to achieve high levels (95 ) of precision [12] It is gathered by various methods (rule based, probability based, and memory based being most common) all of which add part of speech tags noun, verb, pronoun etc. to the original text. Eric Brill s [13][14] freely available rule based POS tagger was used. Although it is slow, and perhaps not as accurate as some modern, commercially available taggers, it is well known and initially seemed adequate. Index expressions The second aspect of pre semantic context is the syntactic structure of ....
Brill, E. "A simple rule-based part of speech tagger," in Proceedings of the Third Conference on Applied Natural Language Processing, ACL, Trento, Italy, 1992.
Logic Form Transformation for WordNet Glosses and its Applications: .. - Rus (2001) (Correct)
....this tagger the parser would generate a wrong parse tree for this gloss and consequently a wrong logic form would be derived. A solution to improve the accuracy of assigned tags is imposed. The state of the art in part of speech tagging is around 95 accuracy for rule based part of speech taggers [4] and stochastic taggers [34] As pointed out in [34] the convergence of accuracy of di erent approaches to tagging can be explained by either that all techniques miss the right predictors to cover the residue, or more likely the performance of corpus based algorithms cannot be higher due to ....
....of the art taggers to improve the performance. If the two taggers agree we assess that tag as being correct. For words that have di erent tags we ask the user to manually decide which one is correct or not. If we reconsider the previous example and tag the gloss of abbey:n#3 using Brill s tagger [4] and MXPOST tagger [34] we obtain the following tags: MXPOST : a DT monastery NN ruled V BN by IN an DT abbot JJ Except the tag for the last word, abbot, the two taggers agree. The tag for abbot is automatically assigned using a second voting scheme between Brill s tagger and WordNet tags: ....
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Eric Brill. A simple rule-based part of speech tagger. In Proceedings of the Third Conference on Applied Natural Language Processing, pages 152-155, 1992.
On the Implementation of an Inference Algorithm in Java - Rus (1999) (Correct)
....helm of the Securities and Exchange Commission, Chairman Arthur Levitt consolidated control of the SEC s 12 regional and branch oces under ve regional directors. All ve regional directors will report to William McLucas, head of the SEC s enforcement division in Washington. We tagged the text[3], disambiguated[34] and then found the lexical relations among basic concepts and provide our system with 17 concepts for the rst sentence, respectively 8 for the second one. The results are displayed in the rst row of Table 4.3. In the second from left column we have the total number of ....
Brill, E. A simple rule-based part of speech tagger. In Proceedings of the Third Conference on Applied Natural Language Processing (Trento, Italy, 1992).
DEREKO (DEutsches REferenzKOrpus) German Reference .. - Dipper, Kermes.. (2002) (Correct)
....315:000 tokens) novels (approx. 150:000 tokens) and other text types (ap6 prox. 30:000 tokens) The POS taggers are trained with either news texts, texts from novels, or all texts, and their most probable analyses are recorded in the linguistic markup. Currently the tnt and Brill taggers are used [4, 5]. The output of all taggers is combined to achieve a single solution by majority voting [30] and POSs are revised using input from syntactic annotation [22] All information added by the tagging, correction, and voting steps is recorded in the markup so that researchers using DEREKO may access it ....
Eric Brill. A simple rule-based part-of-speech tagger. In Proceedings of ANLP-92, 3rd Conference on Applied Natural Language Processing, pages 152--155, Trento, IT, 1992.
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Brill, Eric, "A simple rule-based part-of-speech tagger, " Proc. of Third Conf. on Applied Natural Language Processing, ACL, Trent, Italy, pp.152-155, 1992.
Intelligent Indexing and Semantic Retrieval of Multimodal.. - Srihari, Zhang, Rao (1999) (8 citations) (Correct)
....Parser Named Entity Tagger WordNet Part of Speech Matcher Fig. 5. Architecture of the semantic text indexing system The following are the key phases in semantic indexing of documents. Identiy Objects: To identify objects within a document, we first used a rule based Part of Speech Tagger [6] to tag each term in the to kenized document. The identification is done using regular expressions involving the POS tags, and consists of 6 possible patterns ranging from don t care patterns such as modal words to noun and verb group patterns. Each object consists of a head and a list of ....
E. Brill. A simple rule-based part of speech tagger. In Proceedings of the Third Conference on Applied Natural Language Processing ACL., 1992.
Large Scale Unstructured Document Classification Using.. - Park, Zhang (2003) (2 citations) (Correct)
....2. NP He] VP reckons] NP the current deficit] VP will narrow] PP to] NP only # 1.8 billion ] PP in] NP September] O. In order to chunk the sentences in the documents, the lexical information and the POS (part of speech) information on the contextual words are required. Brill s tagger [3] is used to obtain POS tags for each word in the documents. The chunk type of each word is determined by Support Vector Machines trained with the dataset of CoNLL 2000 shared task . Although there are 12 types of phrases in CoNLL 2000 dataset, we consider, in this paper, only five types of ....
E. Brill. A simple rule-based part-of-speech tagger. In Proceedings of ANLP-92, pages 152--155, 1992.
Learning Information Extraction Rules: An Inductive Logic.. - Aitken (2002) (2 citations) (Correct)
....in the sentence word relation, and may also be used as a filtering mechanism, e.g. words marked as determiners may be removed from the learning input. The following techniques may (optionally) be employed in the NL processing stage of our system: Part of speech (POS) tagging: The Brill tagger [1] is used. Morphological analysis: Words are stemmed by the morphological analyser of [10] POS tag convergence: The Brill tags for each major category are replaced by a single tag for each type (i.e. by one tag for all six types of noun) POS filtering: The POS tags are used to exclude ....
Brill E. A simple rule-based part-of-speech tagger. Proc. of ANLP-92, 3rd Conference on Applied Natural Language Processing 1992, pp. 152--155.
Automatic Evaluation and Uniform Filter Cascades for Inducing.. - Melamed (1995) (12 citations) (Correct)
....ways to remap different tag sets into a more general common tag set represent a number of design decisions. Fortunately, BIBLE provided an objective criterion for tag set design, and a fast evaluation method. The English half of the corpus was tagged using Brill s transformation based tagger [Bri92]. The French half was kindly tagged by George Foster of CITI. Then, BIBLE was used to select among several possible generalizations of the two tag sets. The resulting optimal tag set is shown in Table 2. Tag J N NP VBG VBN Table 2: optimal common tag set for POS Filter Meaning ....
E. Brill, "A Simple Rule-Based Part of Speech Tagger," Proceedings of the 3rd Conference on Applied Natural Language Proces6.ing, pp. 152-155, 1992.
Text Classification Using WordNet Hypernyms - Sam Scott Computer (1998) (17 citations) (Correct)
....than a stop list of most frequent words) is applied to the original text. This paper explores the hypothesis that incorporating linguistic knowledge into text representation can lead to improvements in classification accuracy. Specifically, we use part of speech information from the Brill tagger [Brill 92] and the synonymy and hypernymy relations from WordNet [Miller 90] to change the representation of the text from bag ofwords to hypernym density. We report results from an ongoing study in which the hypernym density representation at different heights of generalization is compared to the old ....
....competence humans bring to a classification task enables us to overcome the difficulties posed by the text itself. 3. The Hypernytn Density Representation The algorithm for computing hypernym density requires three passes through the corpus. a) During the first pass, the Brill tagger [Brill 92] assigns a part of speech tag to each word in the corpus. b) During the second pass, all nouns and verbs are looked up in WordNet and a global list of all synonym and hypemym synsets is assembled. Infrequently occurring synsets are discarded, and those that remain form the feature set. A ....
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E. Brill, "A simple rule-based part-of-speech tagger," in Proceedings of ANLP-92, 3rd Conference on Applied Natural Language Processing, Trento, IT, 1992, pp. 152--155. [Online]. Available: citeseer.nj.nec.com/brill92simple.html
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