Triplet Extraction from Triplet Extraction from Sentences Sentences Technical University of Cluj-Napoca Conf. Dr. Ing. Tudor Mureşan “Jožef Stefan” Institute, Ljubljana, Slovenia Assist. Prof. Dr. Dunja Mladenić Blaž Fortuna Marko Grobelnik Lorand Dali June 2008
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Triplet Extraction from Sentences Technical University of Cluj-Napoca Conf. Dr. Ing. Tudor Mureşan “Jožef Stefan” Institute, Ljubljana, Slovenia Assist.
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Triplet Extraction from Triplet Extraction from SentencesSentences
Technical University of Cluj-Napoca Conf. Dr. Ing. Tudor Mureşan“Jožef Stefan” Institute, Ljubljana, Slovenia
Assist. Prof. Dr. Dunja MladenićBlaž FortunaMarko Grobelnik
Lorand Dali June 2008
Location of the project in the Location of the project in the field of Computer Sciencefield of Computer Science
Artificial IntelligenceNatural Language ProcessingMachine Learning
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Motivation of Triplet ExtractionMotivation of Triplet Extraction
Advantages◦ compact and simple representation of the
information contained in a sentence◦ avoids the complexity of a full parse◦ contains semantic information
Applications◦ building the semantic graph of a document◦ summarization◦ question answering
Triplet Extraction – 2 Triplet Extraction – 2 ApproachesApproachesExtraction from the parse tree of the
sentence using heuristic rules◦ OpenNLP – Treebank Parsetree◦ Link Parser – Link Grammar (a type of dependency
grammar)
Extraction using Machine Learning◦ Support Vector Machines (SVM) are used◦ The SVM model is trained on human annotated data
Short review of SVMShort review of SVM
Features of the triplet Features of the triplet candidatescandidatesOver 300 features depending on:Sentence
◦ length of sentence, number of words, etcCandidate
◦ context of Subj, Verb and Obj;◦ distance between Subj, Verb, Obj
Linkage◦ number of links, of link types, nr of links from S, V, O
Block Diagram of QA Block Diagram of QA SystemSystem
Parse and
determine
question type
BuildQuery
SearchTriplets
Question Answer
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