... 113–116,Columbus, Ohio, USA, June 2008.c2008 Association for Computational LinguisticsKernels on Linguistic Structures for Answer Extraction Alessandro Moschitti and Silvia QuarteroniDISI, ... between query and answer, recentwork, e.g. (Shen and Lapata, 2007) has shown that shallow semantic information in the form of predi-cate argument structures (PASs) improves the auto-matic detection ... represent shallow syn-tactic information in the learning algorithm.To experiment with our models, we built twodifferent corpora, WEB-QA and TREC-QA by us-ing the description questions from TREC...
... benchmarkdataset. We close with a summary and conclu-sions.2 Kernels forRelationExtraction Relation extraction aims at learning a relation from a number of positive and negative instancesin natural ... tree kernel outperforms all others by 5.7%F-Measure reaching an F-Measure of 71.2%. Thisresult shows that both types of parse trees containrelevant informationforrelation extraction. The remainder ... suggestingthat both types of trees contain comple-mentary informationforrelation extrac-tion.1 IntroductionThe same semantic relation between entities innatural text can be expressed in...
... incorporating information gained from the textual context of the candidate term. 2 Context information for terms The idea of incorporating context informationfor term extraction came from that ... 'external' information derived from the context of the candidate string. It is embedded to the C-value approach for automatic term recognition (ATR), in the form of weights constructed from statisti- ... Context Informationfor the Extraction of Terms Katerina T. Frantzi Dept. of Computing Manchester Metropolitan University Manchester, M1 5GD, U.K. K. Frantzi@doc. mmu. ac. uk Abstract The information...
... A. Richardella. 2003.Kernel methods forrelation extraction. Jour-nal of Machine Learning Research, pages 1083–1106.Dependency Tree Kernels forRelation Extraction Aron CulottaUniversity of ... In IJCAIWorkshop on Information Integration on the Web.S. Miller, H. Fox, L. Ramshaw, and R. Weischedel.2000. A novel use of statistical parsing to ex-tract informationfrom text. In 6th Applied ... semantic la-bels denoting entity and relation types. WhereasMiller et al. (2000) use a generative model to pro-duce parse information as well as relation informa-tion, we hypothesize that a...
... Knowledge-based weak supervision forinformationextraction ofoverlapping relations. In Proceedings of the 49th An-nual Meeting of the Association for ComputationalLinguistics: Human Language Technologies ... dictionar-ies forinformationextraction by multi-level bootstrap-ping. In AAAI/IAAI, pages 474–479.Chang Wang, James Fan, Aditya Kalyanpur, and DavidGondek. 2011. Relationextraction with relation topics. ... patterns for the relation. 6We averaged the evaluation values in terms of macroaverage over relations before averaging over the datasplits.6Patterns that ambiguously express the relation, for...
... 2008. Self-supervised relationextractionfrom the web. Knowl-edge and Information Systems, 17(1):17–33.Yusuke Shinyama and Satoshi Sekine. 2006. Preemp-tive informationextraction using unrestricted ... to a small number of relation instances and corpora of less than a mil-lion words.Many early algorithms forrelation extraction used little or no syntactic information. For ex-ample, the DIPRE ... extract evidence for a relation from many different documents, and from any genre.3 FreebaseFollowing the literature, we use the term ‘rela-tion’ to refer to an ordered, binary relation be-tween...
... the field labels that are interesting for the domain 227 Proceedings of EACL '99 The Development of Lexical Resources for InformationExtractionfrom Text Combining WordNet and Dewey ... system has been limited for two main reasons. First the in- formation associated to each term is often not de- tailed enough for describing the relations neces- sary for a IE lexicon; secondly ... Lexical Resources Lexical information in IE can be divided into three sources of information (Kilgarriff, 1997): • an ontology, i.e. the templates to be filled; • the foreground lexicon (FL),...
... performance for English-Latvian. 3 Conclusions and Related Information This demonstration paper describes the ACCURAT toolkit containing tools for multi-level alignment and informationextraction ... Association for Computational Linguistics, pages 91–96,Jeju, Republic of Korea, 8-14 July 2012.c2012 Association for Computational LinguisticsACCURAT Toolkit for Multi-Level Alignment and Information ... sentence generation from comparable corpora for improved SMT. Machine Translation, 25(4): 341-375. ACCURAT D2.6 2011. Toolkit for multi-level alignment and informationextractionfrom comparable...
... “deep” linguistic technology and re-dundant Web informationfor Information Extraction tasks.• Our experimental results reveal that relationsare extractable with good precision using linguistic ... onthe Web. Therefore, we do not parse informa-tion from the Web corpus, but from well writtentexts. Particularly, we specifically examine unsu-pervised relationextractionfrom existing texts ... surface patterns from theWeb corpus. Surface patterns from redundancyWeb information are expected to address the datasparseness problem. Wikipedia is currently widelyused information extraction...
... Computational Linguistics, pages 776–783,Prague, Czech Republic, June 2007.c2007 Association for Computational Linguistics Exploiting Syntactic and Shallow Semantic Kernels for Question/Answer ... impact of syntactic and shallow semantic information in automatic classifi-cation of questions and answers and answerre-ranking. We define (a) new tree struc-tures based on shallow semantics encodedin ... syntactic information helps tasks such as question/answer classifi-cation and that shallow semantics gives re-markable contribution when a reliable set ofPASs can be extracted, e.g. from answers.1...