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 OmurContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & AWordNetA semantic lexicon for the English languagePurpose: A combination of dictionary and thesaurus to support automatic text analysis and artificial intelligence applicationsWordNetGroups the meanings of English words into five categoriesNounsVerbsAdjectivesAdverbsFunction words(prepositions, pronouns, determiners)WordNetMeanings are related by Synonymy (Pipe, Tube)Antonymy (Wet, Dry)Hyponymy (Tree, Plant)Meronymy (Ship, Fleet)Morphological relationsContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & AApplication - WordNetWordNet’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 - WordNetReason 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.ContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & AData Structure & MaintenanceWordNet was created and is being maintained at the Cognitive Science Laboratory of Princeton University under the direction of psychology professor George A. MillerDevelopment began in 1985Q: Where do they get the definitions for WordNet?A: Their Lexicographers write themHowever, 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 & MaintenanceIt has its own database structure and library but there are three versions;Windows (Plain files, queries done by Binary Search)UnixProlog 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.ContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & AFrameNetA project housed at the International Computer Science Institute in Berkeley, California which produces an electronic resource based on semantic framesScope of the projectFrameNet Database : Lexicon, Frame Database, Annotated Example SentencesAssociated Software ToolsFrameNetFrameNetFrameNetComparison with WordNet and OntologyLexical units comes with definitionMultiple annotated exampleExamples from natural corporaFrame by frameA network relations between frames Not readily usable as ontology of thingsContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & AApplication - FrameNetOrganize information in terms of case-roles, which helps determine the lexical meaning by the use of conceptual structure provided by FN.KCan 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.KFrameNet annotated data sets are compared against Information extraction patterns. All non-relevant terms of the frames are discarded.Application - FrameNetReason 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.ContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & AData StructureThe 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 wellFrames are added by FrameNet StaffData StructureData structures were initially implemented in SGMLCurrently uses XML and MySQLFrame information kept in a MySQL database such as frame elements, lemmas or lexical unitsIt has a Java GUI to use MySQL DatabaseIt has also its own query language, namely FrameSQLie “find all example sentences containing verbs in the Communication frame whose Addressees are expressed as direct objects”ContentsIntroductionWordNetApplication – WordNetData Structure - WordNetFrameNetApplication – FrameNetData Structure – FrameNetRelevance with IAQ & ARelevance with IAFN and WN are essential resources for Natural Language Processing applications and Information Exaction systems. KFN and WN have been used for information retrieval, word sense
View Full Document