Báo cáo khoa học: "Combining Lexical, Syntactic, and Semantic Features with Maximum Entropy Models for Extracting Relations" pptx

... Combining Lexical, Syntactic, and Semantic Features with Maximum Entropy Models for Extracting Relations Nanda Kambhatla IBM T. J. Watson Research Center 1101 ... observations in section 4. 2 Maximum Entropy models for extracting relations We built Maximum Entropy models for predicting the type of relation (if any) between every pair of mentions within...

Ngày tải lên: 31/03/2014, 03:20

... simple set of features: the article before; the POS before and after; the preposition before and after, and the syntactic category before and after the word be- ing labeled. The features used ... both dependency parses and hierarchical word ontologies into a maximum- entropy- based tagging model that simultaneously labels words with both syntax and semantics. Our findings sh...

Ngày tải lên: 17/03/2014, 04:20

... stemming and lemmati- sation, since the answers do not contain the ques- tion terms “mosquito” (for question 2) and “form” (for question 3), but only their inflected forms “mosquitoes” and “formed”. 6 ... senses, and hence dif- ferent glosses, it is possible to extract several gloss pairs for one and the same lexeme and one and the same pair of resources. It is therefore nec...

Ngày tải lên: 20/02/2014, 07:20

... Figure 2. Both for 10 and 20 frames, the results are better for 50 than for 20 clusters, with small differences between 10 and 20 frames. The results vary between -11.850 and -10.620 (for 5-50 iterations), ... cluster, and not on the verb, 4. selecting a WordNet concept r for each argu- ment slot, e.g. person for the first slot with probability p(person|c 3 , subj-pp.to,...

Ngày tải lên: 08/03/2014, 01:20

... relation between T1 and H (Example 1), and a contradiction between T2 and H (Example 2). As introduced before, our paper proposes an approach to support the participants in forums or debates to ... contradict such argument with opinions against it (Example 2). Since in debates arguments come one after the other, we extract and compare them both with respect to the main issue, and...

Ngày tải lên: 16/03/2014, 20:20

... (Lesk2); FRGL using Lesk3 for all POS tags (Lesk3); using Lesk3 for N, A and R but LIN simi- larity measure for verbs (Lesk3 Lin); using Lesk3 for N, A and R but JCN for verbs (Lesk3 JCN). In ... examples with TransCont. We found that the best results are yielded using the Lesk2/Lesk3 similarity measure for N, A and R POS tagsets, while the Lin and JCN measures yield the...

Ngày tải lên: 17/03/2014, 00:20

... GST-JAK1DN for pJAK1, JAK1, pTYK2 and TYK2, calnexin for pSTAT1, STAT1, pSTAT2, STAT2 and IRF9, in the cytoplasm and poly [ADP-ribose] polymerase 1 for pSTAT1, STAT1, pSTAT2, STAT2 and IRF9 in ... Hauser and Didier Trono (E ´ cole polytechnique fe ´ de ´ rale de Lausanne EPFL, Lab of virology and genetics, Switzerland) for the supplied reagents. We thank Sandra Manthey an...

Ngày tải lên: 23/03/2014, 03:20

... alignments for MK–EN and EN–BG, from which we extracted four conditional lexical translation probabilities: Pr(m|e) and Pr(e|m) for MK–EN, and Pr(b|e) and Pr(e|b) for EN–BG, where m, e, and b stand for ... alignments with good performance in terms of phrase-based transla- tion. In our experiments, we used GIZA++ (Och and Ney, 2003) with standard settings and the grow...

Ngày tải lên: 23/03/2014, 14:20

... once and for all, and quite manageably, for all con- fusion sets; new confusion sets can be added later without any additional training. This feature makes Trigrams a very easily expandable ... two types of features: context words and collocations. Context-word features test for the presence of a particular word within +k words of the target word; collocations test for...

Ngày tải lên: 23/03/2014, 20:21

... Mn 2+ : the k obs at 150 lm GMP is 0.96 min )1 with Mn 2+ and 0.87 min )1 without it, and at 20 lm GMP, the k obs is 0.49 min )1 with Mn 2+ and 0.55 min )1 without it. We conclude that Mn 2+ increases ... expðÀk a  tÞþB expðÀk b  tÞð2Þ A and k a are the percentage and observed rate constant for the fast-reacting pre-RNA, and B and k b are the same parameters for the sl...

Ngày tải lên: 19/02/2014, 07:20