Eric Brill. A Corpus-Based Approach to Language Learning. PhD thesis, University of Pennsylvania, 1993.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....the parser (parser should accept tagger s tag set) 31 it should have compatible tag sets One extra feature we watch for was to be able to easily modify the tagger to t our speci c data. There are many taggers available out there. We chose to use MXPOST tagger [34] and Brill s POS tagger [4][5][6] 7] as being the ones the most respect our guiding principles described before. MXPOST is a statistical tagger and it was trained on sections from Wall Street Journal corpus. MXPOST is a statistical tagger with a Maximum Entropy model that uses many contextual features (the word contains ....

Eric Brill. A Corpus-based Approach to Language Learning. PhD thesis, Department of Computer and Information Science, University of Pennsylvania, 1993.

....key button K, K is the key button, n is the length of the considering token. 3.3.2 Error Correction for Thai Key Prediction In some cases of Thai character sequence, the tri gram model fails to predict the correct key. To correct these errors, the error correction rule method proposes by Brill [1, 2] is employed. 3.3.2.1 Error correction Rule Extraction Only the prediction errors after applying tri gram prediction to the training corpus are considered to prepare the error correction rule. The left and right three keys input Language Identification Key Input Thai Key Prediction Output ....

Brill, E. (1993) A Corpus-Based Approach to Language Learning. Ph.D. Dissertation, University of Pennsylvania.

....Works Language Identification Key Input Thai Key Prediction Output Eng Yes Thai 3.3.2 Error Correction for Thai Key Prediction In some cases of Thai string sequences, the trigram model fails to predict the correct key. To correct these errors, the error correction rules as in [1] and [2] are employed. 3.3.2.1 Error correction Rule Extraction After applying trigram prediction to the training set, prediction errors happen. The left and right three keys input around each error character and the correct pattern corresponding with the error will be collected as an error correction ....

Brill, E. (1993) A Corpus-Based Approach to Language Learning. Ph.D. Dissertation, University of Pennsylvania.

....reach an F measure of 92 in the test set. In fact the HCRC LTG system, described in the next section, is the proof of this hypothesis. Alembic In MUC 6 evaluations, MITRE participated with the Alembic system [Aberdeen et al. 1995] using transformation based error driven learning algorithm of Brill [1993]. Their performance was in middle 80s. RoboTag Bennett et al. 1997] used binary decision trees using C4.5 [Quinlan, 1986] for name tagging task in the RoboTag system. The decision tree decides whether it is a name boundary or not. They use features indicating semantic properties (like first ....

Brill, Eric 1993. A Corpus-Based Approach to Language Learning. Ph.D. Dissertation, Department of Computer Science, University of Pennsyl- vania.

....17.33 79.20 5.97 Zero Cross Brack DOP P S 1.33 20.00 21.33 6.93 5.65 Exact Match DOP 58.67 68.00 9.33 63.33 3. 22 Table 2: DOP versus Pereira and Schabes on Bod s Data A few sentences were not parsable; these were assigned right branching period high structure, a good heuristic (Brill, 1993). We also ran experiments using Bod s data, 75 sentence test sets, and no limit on sentence length. However, while Bod provided us with his data, he did not provide us with the split into test and training that he used; as before we used ten random splits. The results are disappointing, as shown ....

Eric Brill. 1993. A Corpus-Based Ap- proach to Language Learning. Ph.D. thesis, University of Pennsylvania.

....system, Alembic [1,7] to new tasks: the Message Understanding Conferences 0VIUC5 and MUC6) and the TIPSTER Multi lingual Entity Task (MET1) See [6] for an overview and history of MUC6 and the Named Entity Task . The Alembic text processing system applies Eric Brill s notion of ru e sequences [2,3] at almost every one of its processing stages, from part ofspeech tagging to phrase tagging, and even to some portions of semantic interpretation and inference. While its name indicates its lineage, we do not view the Alembic Workbench as wedded to the Alembic text processing system alone. We ....

Eric Brill. 1993. A Corpus-Based Approach to Language Learning. Ph.D. thesis, University of Pennsylvania, Philadelphia, Penn.

....whether the preposition attaches to the preceding NP or to the V. Since most prepositions attach to the NP, it may always make the choice to attach the preposition to the NP, but in the case of with, this would be a bad choice since with is an exception, attaching more commonly to the verb [Bri93] At the next level, a more comprehensive parser will employ some more sophisticated means of disambiguation, such as the encoding of semantic information, e.g. case frames 16 for verbs, or the use of co occurrence and frequency based techniques, which can improve a parser s performance by ....

....this kind of knowledge, recent work has shown that more superficial forms of knowledge can be used successfully. Various researchers have attempted to resolve prepositional phrase attachment ambiguities by means of statistical approaches involving semantic word classes, e.g. WAB 91] BPV91] Bri93] HR93] These probabilistic models produce the interpretation with the greatest likelihood of occurrence. 26 3.1 Rule Based Approaches Brill and Resnik [BR94] describe a rule based approach to disambiguation of prepositional phrase attachment, which uses information automatically extracted ....

E. Brill. A Corpus based Approach to Language Learning. PhD thesis, Dept. of Computer and Information Science, University of Pennsylvania, 1993. 96

....reach an F measure of 92 in the test set. In fact the HCRC LTG system, described in the next section, is the proof of this hypothesis. Alembic In MUC 6 evaluations, MITRE participated with the Alembic system [Aberdeen et al. 1995] using transformation based error driven learning algorithm of Brill [1993]. Their performance was in middle 80s. RoboTag Bennett et al. 1997] used binary decision trees using C4.5 [quinlan, 1986] for name tagging task in the RoboTag system. The decision tree decides whether it is a name boundary or not. They use features indicating semantic properties (like first ....

Brill, Eric 1993. A Corpus-Based Approach to Language Learning. Ph.D. Dissertation, Department of Computer Science, University of Pennsyl- vania.

....Speech Tagging After identifying fields of interest, our feature extraction algorithms perform part of speech tagging. The part of speech tagger is a rule based system for tagging English parts of speech. This system is based on the SemanTag system developed in [7] which in turn is based on [3] [4] [5] The tagger uses three levels of rule sets to determine the part of speech of each word, and tags words with their English part of speech tag, as specified in the Brown tagset [12] DT determiner IN preposition or subordinating conjunction NN noun singular or mass PP personal ....

E. Brill. A corpus-based approach to Language learning. PhD thesis, University of Pennsylvania, Department of Computer and Information Science, 1993.

....applications have a manageable number of subgrammars corresponding to different, easily identified semantic concepts. However, in general, automatic parsing of corpora into phrases and clustering of phrases will be needed to design layered bigrams optimally, perhaps using techniques described in [2], 3] or [5] Our definition of a layered bigram is somewhat weaker than that of [11] because in our case the probabilities that are internal to a bigram node are independent of its predecessor nodes; there is no conditioning on the children of these nodes. We have implemented a recognition ....

Eric Brill. A Corpus-Based Approach to Language Learning. PhD thesis, University of Pennsylvania, 1993.

....reach an F measure of 92 in the test set. In fact the HCRC LTG system, described in the next section, is the proof of this hypothesis. Alembic In MUC 6 evaluations, MITRE participated with the Alembic system [Aberdeen et al. 1995] using transformation based error driven learning algorithm of Brill [1993]. Their performance was in middle 80s. RoboTag Bennett et al. 1997] used binary decision trees using C4.5 [Quinlan, 1986] for name tagging task in the RoboTag system. The decision tree decides whether it is a name boundary or not. They use features indicating semantic properties CHAPTER 7. NAME ....

Brill, Eric 1993. A Corpus-Based Approach to Language Learning. Ph.D. Dissertation, Department of Computer Science, University of Pennsylvania.

....generates rules automatically. The procedures are mainly divided into two parts; preprocessing, and automatic rule generation. The preprocessing steps will be explained in Section 2.1. Then the automatic rule generation steps, the general idea of which originated from Brill s part of speech tagger [3], will be described in Section 2.2. 2.1. Preprocessing In this system, an untagged training data le is passed through the initial NE recogniser. The system separates all punctuation marks from their adjacent words, and then treats these punctuation marks as words. Training data with initial NE ....

E. Brill. A Corpus-Based Approach to Language Learning. PhD thesis, University of Pennsylvania, 1993.

..... Translation is provided by Systran, http: www.systransoft.com sum of all the scores of content bearing terms in the sentence. These heuristics are implemented in separate modules using inputs from preprocessing modules such as tokenizer, part ofspeech tagger [6], morphological analyzer, term frequency and tf idf weights calculator, sentence length calculator, and sentence location identifier. 3. COMPARING the EFFECTIVENESS of HEURISTICS Initially, we implemented for SUMMARIST a straightforward linear combination function, in which we specified the ....

Brill, E. 1992. A Corpus-Based Approach to Language Learning. Ph.D. dissertation, University of Pennsylvania.

....have to be an element of the list of tags returned by the MA for the given word. That is why the purely subtag independent strategy is modified by the so called Valid Tag Combination (VTC) strategy. Rule based approach The supervised transformation based error driven learning method described in [Brill, 1993] is classified as corpus based; however, we have to stress that it employs not only a small annotated corpus but a large unannotated corpus as well. A pool of allowable lexical and contextual transformations is predetermined by templates operating on word forms and word tokens, respectively. A ....

....the tagging procedure. The demand for more training data in case of a tagger with morphological preprocessing becomes more intensive. RB STRATEGY For Czech, we take the rule based tagger as is (designed for English) i.e. with the prespecified lexical contextual templates of the following form ([Brill, 1993]) The strategy of a rule based tagger determines the usage of annotated and unannotated corpora. The annotated corpus is being split into two parts of equal size. The first of these parts is used for learning the rules to predict the most probable tag for unknown words (lexical rules) and the ....

E. Brill. A Corpus-Based Approach to Language Learning. A dissertation in Department of Computer and Information Science, University of Pennsylvania, Philadelphia, USA, 1993.

....Therefore their membership value is increased. If the parser, however, does not succeed in parsing the sentence, the learning component is called: 13 Kbler Learning Lexicalised Grammar for German . As a first step, every word in the sentence is tagged. The formalism used for tagging will be Brill s (1993, 1995) transformation based error driven tagger. Unlike other approaches to learning using constituent based grammars, this system does not use the wordclass information to restrict the roles, a word can play in the parse. Rather it takes this information as a starting point in the search for ....

Brill, E. (1993). A Corpus-Based Approach to Language Learning (Ph.D. thesis). Philadelphia: University of Pennsylvania, Department of Computer and Information Science.

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Eric Brill. A Corpus-Based Approach to Language Learning. PhD thesis, University of Pennsylvania, 1993.

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Brill, E. (1993). A corpus-based approach to language learning (Ph.D. Thesis). Philadelphia, PA: Department of Computer and Information Science, University of Pennsylvania. Available at: http://www.cs.jhu.edu/~brill/dissertation.ps

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E. Brill, "A corpus-based approach to Language learning", PhD. Dissertation, Department of Computer and Information Science, University of Pennsylvania, 1993.

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Eric Brill. A Corpus-Based Approach to Language Learning. PhD thesis, University of Pennsylvania, 1993.

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Brill, E. (1993) A Corpus-Based Approach to Language Learning. Ph.D. Dissertation, University of Pennsylvania.

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E. Brill, A Corpus-Based Approach to Language Learning, Ph.D. thesis, University of Pennsylvania, 1993.

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E. Brill. A Corpus-Based Approach to Language Learning. PhD thesis, University of Pennsylvania, 1993.

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Brill, Eric, "A Corpus-Based Approach to Language Learning," Ph.D. Thesis, University of Pennsylvania, 1993.

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Eric Brill (1993). A Corpus-BasedApproach to language Learning. Ph.D. thesis, University of Pennsylvania.

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Brill, E. 1993. A Corpus-Based Approach to Language Learning. Ph.D. diss., University of Pennsylvania.

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