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WordNet & FrameNetContentsWordNetSlide 4Slide 5Slide 6Application - WordNetSlide 8Slide 9Data Structure & MaintenanceSlide 11Slide 12FrameNetSlide 14Slide 15Slide 16Slide 17Application - FrameNetSlide 19Slide 20Data StructureSlide 22Slide 23Slide 24Relevance with IASlide 26DiscussionThank You For Listening…Jennie Ning ZhengLinda MelchorFerhat OmurContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & AWordNetA semantic lexicon for the English languagePurpose: A combination of dictionary and thesaurus to support automatic text analysis and artificial intelligence applicationsWordNetGroups the meanings of English words into five categoriesNounsVerbsAdjectivesAdverbsFunction words(prepositions, pronouns, determiners)WordNetMeanings are related by Synonymy (Pipe, Tube)Antonymy (Wet, Dry)Hyponymy (Tree, Plant)Meronymy (Ship, Fleet)Morphological relationsContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & AApplication - WordNetWordNet’s hierarchical structure can help in the creation faceted categories, which are essential for faceted metadata and search functions. Words from a structured collection are compared to high-level category labels of WordNet’s lexicon.Subsets of the most frequently occurring categories are retained.Categories related to ambiguous words are discarded.High-level hierarchy labels that are to general or broad are discarded as well.Application - WordNetReason for using WordNet?Allows for efficient navigation within and across lexical data due the rigorous structure of its semantic tagging Hypernym (IS A) relations are most commonly used and easiest to integrate into Information Extraction and browsing/search systems, making it easier to find synonyms and near synonyms of words. Currently, there has been a movement to create multilingual WordNets with the goal of enhancing cross-lingual information retrieval systems. WN provides a platform for representing the lexical knowledge between different languages.ContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & AData Structure & MaintenanceWordNet was created and is being maintained at the Cognitive Science Laboratory of Princeton University under the direction of psychology professor George A. MillerDevelopment began in 1985Q: Where do they get the definitions for WordNet?A: Their Lexicographers write themHowever, many different dictionaries and sources were used and many others are still being used to expand the WordNet library.The database contains about 150,000 words organized in over 115,000 synsets for a total of 207,000 word-sense pairsData Structure & MaintenanceIt has its own database structure and library but there are three versions;Windows (Plain files, queries done by Binary Search)UnixProlog However, there are different API’s exist to use WordNet database which are written in Java or C#, and different types of databases exist such as XML, MySQL, PostgreSQL and many others as well to store WordNet data.ContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & AFrameNetA project housed at the International Computer Science Institute in Berkeley, California which produces an electronic resource based on semantic framesScope of the projectFrameNet Database : Lexicon, Frame Database, Annotated Example SentencesAssociated Software ToolsFrameNetFrameNetFrameNetComparison with WordNet and OntologyLexical units comes with definitionMultiple annotated exampleExamples from natural corporaFrame by frameA network relations between frames Not readily usable as ontology of thingsContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & AApplication - FrameNetOrganize information in terms of case-roles, which helps determine the lexical meaning by the use of conceptual structure provided by FN.KCan be applied to NLP systems because of its potential to find the arguments of a collection through the use of word sense and sentence examples.KFrameNet annotated data sets are compared against Information extraction patterns. All non-relevant terms of the frames are discarded.Application - FrameNetReason for using FrameNet?The lexicon and pattern sets provided by FN make it possible for natural language processing systems to generate more precise results than those allowed by WordNet.FN consists of machine readable terms that provide sentence examples extracted from natural corpora, which make it possible to provide meaning to terms related to frames.ContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & AData StructureThe development of the theory of Frame Semantics began more than 25 years ago, however until 1997 there were no implementations British National Corpus and Linguistic Data Consortium were used to create the database and they plan to add American National Corpus data as wellFrames are added by FrameNet StaffData StructureData structures were initially implemented in SGMLCurrently uses XML and MySQLFrame information kept in a MySQL database such as frame elements, lemmas or lexical unitsIt has a Java GUI to use MySQL DatabaseIt has also its own query language, namely FrameSQLie “find all example sentences containing verbs in the Communication frame whose Addressees are expressed as direct objects”ContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & ARelevance with IAFN and WN are essential resources for Natural Language Processing applications and Information Exaction systems. KFN and WN have been used for information retrieval, word sense


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UMD INFM 700 - WordNet & FrameNet

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