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  • Participants
    Parsing Project 3 Participants 4 Franklin Sentence Parsing Program 5 CL Research DIMAP 6 DIMAP Dictionary 7 DIMAP Dictionary Entry 8 Definition Parsing 9 Definition Parsing Process 10 Untitled 11 Examination of Parsing Results 12 Lexicographer Functionality 13 Definition Comparison

    Original URL path: http://www.clres.com/dppdemo/fslide3.html (2016-02-11)
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  • DIMAP Dictionary
    Dictionary Parsing Project 3 Participants 4 Franklin Sentence Parsing Program 5 CL Research DIMAP 6 DIMAP Dictionary 7 DIMAP Dictionary Entry 8 Definition Parsing 9 Definition Parsing Process 10 Untitled 11 Examination of Parsing Results 12 Lexicographer Functionality 13 Definition

    Original URL path: http://www.clres.com/dppdemo/fslide6.html (2016-02-11)
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  • CL Research Software Feedback
    Please return to the feedback form and enter clr in the Spam Block field

    Original URL path: http://www.clres.com/db/feedback0.php (2016-02-11)
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  • Category » Represenation of meaning « @ The Clog
    rest of this entry Represenation of meaning digraph analysis frame elements FrameNet semantic relations Electronic dictionaries of the future Posted in August 5 2009 4 42 pmh Ken 1 Comment Current electronic dictionaries are presently little more than transcriptions of paper dictionaries To be sure they have a lot more information than is present in the print versions But they are not really designed to support natural language processing The major needs of the future are 1 a set of instances illustrating each sense of Read the rest of this entry Construction patterns Electronic dictionaries Represenation of meaning Usage examples word sense disambiguation frame elements FrameNet semantic dependency graphs sentence dictionary Categories Select Category Construction patterns 2 Content Analysis 1 digraph analysis 7 Electronic dictionaries 4 Usage examples 2 Prepositions 5 Represenation of meaning 2 Semantic Analysis 1 Uncategorized 2 Semantic Primitives 1 word sense disambiguation 4 Tags cognitive neuroscience collocational features computational lexicons dictionary clues digraph analysis Firth maxim frame to frame relations frame elements FrameNet inference steps MCCA meaning fragments natural language processing ontologies preposition classes preposition complements preposition meaning representation of meaning semantic dependency graphs semantic relations semantic role features sentence dictionary strong components syntactic features taxonomies

    Original URL path: http://www.clres.com/blog/?cat=10 (2016-02-11)
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  • More circularities in the frame element hierarchy @ The Clog
    Relation seems to be the most general term Both Relation and Relationship are defined as the way in which two or more people or things are connected suggesting that Relation should be given the hypernym Manner Evaluee Victim Patient Entity This circularity arose when Patient was assigned the hypernym Entity based on its definitions in 11 frames mostly in some variation of the entity that is being acted on The link from Entity to Evaluee comes from the frame to frame relation Aesthetics INHERITS Desirability and from Labeling USES Judgment communication The link from Evaluee to Victim comes from the frame to frame relation Corporal punishment INHERITS Cause harm Making Evaluee the more general frame element in Desirability and Judgment communication seems to have been a slightly inappropriate assignment To break the circularity Evaluee was deleted as the hypernym of Entity making Entity the more primitive frame element where Evaluee will eventually inherit Entity via the links from Evaluee to Victim to Patient to Entity Degree Amount of information This circularity arose when Amount of information was given the hypernym Degree It s definition The amount of information exchanged when communication occurs was not informative but the example He never really Amount of information fully COMMUNICATED his intentions suggests that the meaning of this frame element can be suitably characterized as Degree The reverse link Degree having the hypernym Amount of information arose from the frame to frame relations Attempt suasion USES Communication Communication noise INHERITS Communication Suasion USES Communication and Volubility USES Communication In these cases Communication is the more general frame so the use of Amount of information as the frame element seems overly specific To break this circularity Amount of information was removed as the hypernym of Degree digraph analysis digraph analysis frame to frame relations FrameNet

    Original URL path: http://www.clres.com/blog/?p=83 (2016-02-11)
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  • The Clog › Lost Password
    The Clog Please enter your username or email address You will receive a link to create a new password via email Username or E mail Log in Back to The

    Original URL path: http://www.clres.com/blog/wp-login.php?action=lostpassword (2016-02-11)
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  • Electronic dictionaries of the future @ The Clog
    of routines to extract and make use of this information More can be done in this area Representation mechanisms Each sense needs a representation of its meaning that can be plugged into a representation of a sentence where it s used Clearly the definition is one such representation and the design of definitions has generally been intended so that they can be substituted for a use A lot of effort has gone into various representational formalisms A lot of this has been done in the development of ontologies creating a logic style representation This seems too strong and doesn t provide the wiggle room in the haziness that constitutes a meaning I like FrameNet and frame semantics However these frames are not really set up to represent the meaning of a sense in a pluggable form Consider the meaning of a preposition Within frame semantics we can somewhat safely state that each preposition sense corresponds to a frame element with the preposition object acting as a filler for the slot that the frame element provides When we start moving to longer pieces of text including more elaborate preposition definitions we can t follow this simple plug and play The FrameNet folks have attempted to analyze texts into semantic dependency graphs and this approach seems to hold together But when we consider complex definitions we need to consider some sort of compositional approach To accomplish this we need to perform some filling of frames along the way A good example of this is to be found in the definitions of spatial prepositions FrameNet has two frame elements Direction and Distance Many of the definitions fill in values for these frame elements which can then be dragged along in building representations of a sentence We find the same phenomenon in definitions of

    Original URL path: http://www.clres.com/blog/?p=24 (2016-02-11)
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  • Category » Construction patterns « @ The Clog
    Read the rest of this entry Construction patterns Electronic dictionaries Represenation of meaning Usage examples word sense disambiguation frame elements FrameNet semantic dependency graphs sentence dictionary Preposition construction patterns Posted in August 1 2009 5 23 pmh admin No Comments A construction pattern attempts to characterize the usage of each sense in such a way that it can be used to disambiguate among the several senses of a word Constructions are becoming more widely used as described in Atkins Rundell The Oxford Guide to Practical Lexicography The authors describe patterns for verbs nouns adjectives Read the rest of this entry Construction patterns Prepositions dictionary clues word sense disambiguation Categories Select Category Construction patterns 2 Content Analysis 1 digraph analysis 7 Electronic dictionaries 4 Usage examples 2 Prepositions 5 Represenation of meaning 2 Semantic Analysis 1 Uncategorized 2 Semantic Primitives 1 word sense disambiguation 4 Tags cognitive neuroscience collocational features computational lexicons dictionary clues digraph analysis Firth maxim frame to frame relations frame elements FrameNet inference steps MCCA meaning fragments natural language processing ontologies preposition classes preposition complements preposition meaning representation of meaning semantic dependency graphs semantic relations semantic role features sentence dictionary strong components syntactic features taxonomies tweets Twitterverse word

    Original URL path: http://www.clres.com/blog/?cat=4 (2016-02-11)
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