a method for word sense disambiguation of unrestricted text

... lexical knowledge methods for word sense disambiguation. Computational Linguistics. J. Stetina, S. Kurohashi, and M. Nagao. 1998. General word sense disambiguation method based on a full ... for word sense disambiguation. Com- putational Linguistics, 18(1):1-30. R. Mihalcea and D.I. Moldovan. 1999. An au- tomatic method for generating sense tagged corpora. In Proceedings of ... semantically close. For appli- cations such as machine translation, fine grain disambiguation works well but for information extraction and some other applications this is an overkill, and...

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Ngày tải lên: 23/03/2014, 17:20

... sense of a target word, using WordNet-based measures of seman- tic relatedness (Patwardhan et al., 2003). SenseRelate::TargetWord is a Perl pack- age that implements this algorithm. The disambiguation ... Sessions, pages 73–76, Ann Arbor, June 2005. c 2005 Association for Computational Linguistics SenseRelate::TargetWord – A Generalized Framework for Word Sense Disambiguation Siddharth Patwardhan School ... lexical sample format, which is an XML–based format that has been used for both the S ENSEVAL-2 and SENSEVAL-3 exercises. A file in this format includes a number of instances, each one made up of...

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Ngày tải lên: 23/03/2014, 16:20

... their aligned translations (and probabil- 319 algorithm parameters in machine learning of language. Machine Learning, pages 84–95. I. Dagan and A. Itai. 1994. Word sense disambiguation using a second ... state -of- the-art systems for all languages, ex- cept for Spanish where the results are very similar. As all steps are run automatically, this multilingual approach could be an answer for the acquisition ... SemEval systems as well as the three flavors of the ParaSense system, were trained on the same Europarl data, the scores illus- trate the potential advantages of using a multilingual approach. Although...

Ngày tải lên: 20/02/2014, 05:20

... This gave a set of 6 nouns for SENSEVAL-2 and 9 nouns for SENSEVAL- 3. For each noun, we gathered a maximum of 500 parallel text examples as training data, similar to what we had done in (Chan and ... 200 5a. Scaling up word sense disambiguation via parallel texts. In Proc. of AAAI05. Yee Seng Chan and Hwee Tou Ng. 2005b. Word sense disambiguation with distribution estimation. In Proc. of IJCAI05. Pedro ... @comp.nus.edu.sg Abstract Instances of a word drawn from different domains may have different sense priors (the proportions of the different senses of a word) . This in turn affects the accuracy of word sense...

Ngày tải lên: 08/03/2014, 02:21

... be available for many examples. The problem of data sparse- ness increases as more knowledge is exploited and this can cause problems for the machine learning algorithms. A final disadvantage ... Machine Translation. Academic Press, Great Britain. Abolfazl K. Lamjiri, Osama El Demerdash, Leila Kos- seim. 2004. Simple features for statistical Word Sense Disambiguation. Proceedings of ... English Lexical Sample Task. Proceedings of Senseval-3: 3rd International Workshop on the Evaluation of Systems for Semantic Analysis of Text, Barcelona, pages 25-28. Saif Mohammad and Ted Pedersen....

Ngày tải lên: 08/03/2014, 02:21

... and accuracy improvement is less than 1% after all the available WSJ adaptation examples are added as additional training data. To obtain a clearer picture of the adaptation process, we discard ... in BC and WSJ, average MFS accuracy, average number of BC training, and WSJ adaptation examples per noun. data, and the rest of the WSJ examples are desig- nated as in-domain adaptation data. The ... 100 WSD Accuracy (%) Percentage of adaptation examples added (%) a- c a r a- truePrior Figure 2: Adaptation process for all 21 nouns. of the BC training examples. At each adaptation iter- ation, WSJ adaptation...

Ngày tải lên: 08/03/2014, 02:21

... the official training data so that we can do a fair comparison between the accuracy of the parallel text alignment approach versus the manual sense- tagging approach. After training a WSD classifier ... automobile races) could be found in the parallel corpora. To ensure a fairer comparison, for each of the 10-trial manually sense- tagged training data that gave rise to the ac- curacy figure M2 of a ... empirical study to evaluate an approach of automatically acquiring sense- tagged training data from English-Chinese parallel corpora, which were then used for disam- biguating the nouns in the SENSEVAL-2...

Ngày tải lên: 08/03/2014, 04:22

... were discarded. tions caused by tagging or lemmatization errors, we manually corrected any bad tags and lemmas for the target instances. 4 Sense Paraphrases For word sense disam- biguation tasks, ... much background information is available, i.e., knowl- edge of the prior sense distribution available and type of sense paraphrases used. In Model I and Model II, the sense paraphrases are obtained from WordNet, ... Chang. 2009. Plda: Parallel latent dirichlet allocation for large-scale applications. In Proc. of 5th Interna- tional Conference on Algorithmic Aspects in Infor- mation and Management. Software...

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... value between vl and nj. We recall that wp and nq are semantically re- lated if w~i and nq are semantically related and (wv,n q) and (w'pi,nq) are semantically similar. (a) ' and ... These algorithms assign each instance of an ambiguous word to a known sense definition based solely on the values of automatically iden- tifiable features in text. Their methods are per- haps ... This algorithm requires a small number of training examples to serve as a seed. The result shows that the average percentage attained was 96.1% for 12 nouns when the training data was a 460...

Ngày tải lên: 08/03/2014, 21:20

... (Kingsbury and Palmer, 2002) and Penn Treebank (Marcus et al., 1993). Such projects typically involve a formal model (such as a controlled vocabulary of thematic roles) and a corpus of text that has ... (equivalent to Figure 2) as configured for a particular Aesop fable. 3. The procedure for reading a text for impor- tant named entities, and formally declaring these named entities for the story graph. 4. ... labeling of verb frames, thematic roles, temporal structure, modal- ity, causality and other features. This type of anno- tation allows for machine learning on the thematic dimension of narrative...

Ngày tải lên: 17/03/2014, 02:20

... each word, training and test instances tagged with WordNet senses are provided. There are an av- erage of 7.8 senses per target word type. On average 109 training instances per target word are ... Special issue on SEN- SEVAL. Hoa Trang Dang and Martha Palmer. Combining contextual features for word sense disambigua- tion. In Proceedings of the SIGLEX/SENSEVAL Workshop on Word Sense Disambiguation: ... are available. Note that we used the set of sense classes from Sen- seval’s ”fine-grained” rather than ”coarse-grained” classification task. The KPCA-based model achieves the highest ac- curacy, as...

Ngày tải lên: 20/02/2014, 16:20