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Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F12%3A10130035%21RIV13-GA0-11320___
rdf:type
skos:Concept n13:Vysledek
rdfs:seeAlso
http://aclweb.org/anthology-new/E/E12/E12-1085.pdf
dcterms:description
Low interannotator agreement (IAA) is a well-known issue in manual semantic tagging (sense tagging). IAA correlates with the granularity of word senses and they both correlate with the amount of information they give as well as with its reliability. We compare different approaches to semantic tagging in WordNet, FrameNet, Prop- Bank and OntoNotes with a small tagged data sample based on the Corpus Pattern Analysis to present the reliable information gain (RG), a measure used to optimize the semantic granularity of a sense inventory with respect to its reliability indicated by the IAA in the given data set. RG can also be used as feedback for lexicographers, and as a supporting component of automatic semantic classifiers, especially when dealing with a very fine-grained set of semantic categories. Low interannotator agreement (IAA) is a well-known issue in manual semantic tagging (sense tagging). IAA correlates with the granularity of word senses and they both correlate with the amount of information they give as well as with its reliability. We compare different approaches to semantic tagging in WordNet, FrameNet, Prop- Bank and OntoNotes with a small tagged data sample based on the Corpus Pattern Analysis to present the reliable information gain (RG), a measure used to optimize the semantic granularity of a sense inventory with respect to its reliability indicated by the IAA in the given data set. RG can also be used as feedback for lexicographers, and as a supporting component of automatic semantic classifiers, especially when dealing with a very fine-grained set of semantic categories.
dcterms:title
Managing Uncertainty in Semantic Tagging Managing Uncertainty in Semantic Tagging
skos:prefLabel
Managing Uncertainty in Semantic Tagging Managing Uncertainty in Semantic Tagging
skos:notation
RIV/00216208:11320/12:10130035!RIV13-GA0-11320___
n13:predkladatel
n14:orjk%3A11320
n3:aktivita
n16:P
n3:aktivity
P(7E09003), P(GBP103/12/G084)
n3:dodaniDat
n4:2013
n3:domaciTvurceVysledku
n12:8241651 n12:9873112 n12:1753061
n3:druhVysledku
n11:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n15:predkladatel
n3:idSjednocenehoVysledku
148012
n3:idVysledku
RIV/00216208:11320/12:10130035
n3:jazykVysledku
n10:eng
n3:klicovaSlova
tagging; semantic; uncertainty; managing
n3:klicoveSlovo
n5:semantic n5:tagging n5:uncertainty n5:managing
n3:kontrolniKodProRIV
[1C9F9846C0D6]
n3:mistoKonaniAkce
Avignon, France
n3:mistoVydani
Avignon, France
n3:nazevZdroje
Proceedings of 13th Conference of the European Chapter of the Association for Computational Linguistics
n3:obor
n17:IN
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:projekt
n18:GBP103%2F12%2FG084 n18:7E09003
n3:rokUplatneniVysledku
n4:2012
n3:tvurceVysledku
Kríž, Vincent Cinková, Silvie Holub, Martin
n3:typAkce
n21:CST
n3:zahajeniAkce
2012-04-23+02:00
s:numberOfPages
11
n9:hasPublisher
Association for Computational Linguistics
n6:isbn
978-1-937284-19-0
n22:organizacniJednotka
11320