disambiguation task
Evaluating a Semantic Network Automatically Constructed from Lexical Co occurrence on a Word Sense Disambiguation Task
... the disambiguation algorithms described above in Section ...the disambiguation algorithms described above, with the following modification: when confronted with a pair of semantically related polysemous ...
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A Vector Semantics Approach to the Geoparsing Disambiguation Task for Texts in Spanish
... location disambiguation in news documents that uses a vector-semantic representation learned from information sources that include events and geographic descriptions, in order to obtain a ranking for the possible ...
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SemEval 2007 Task 06: Word Sense Disambiguation of Prepositions
... are considered in relation to verbs. While linguistic theory focuses on subjects and objects as important verb arguments, quite frequently there is an additional oblique argument realized in a prepositional phrase. But ...
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DECISION LISTS FOR LEXICAL AMBIGUITY RESOLUTION: Application to Accent Restoration in Spanish and French
... In a study comparing results for 20 words in a binary homograph disambiguation task, based strictly on words in local 4-4 word context, the following differences were observed between an[r] ...
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Disambiguation of Preposition Sense Using Linguistically Motivated Features
... We chose maximum entropy (Berger et al., 1996) as our primary classifier, since it had been successfully applied by the highest performing systems in both the SemEval-2007 preposition sense disambiguation ...
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Anveshan: A Framework for Analysis of Multiple Annotators’ Labeling Behavior
... tion task. The annotation data comes from a word sense disambiguation task for pol- ysemous words, annotated by both trained annotators and untrained annotators from Amazon’s Mechanical ...
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Deriving de/het gender classification for Dutch nouns for rule based MT generation tasks
... contextual disambiguation task, and we can evaluate three aspects of the performance of our method: (a) what coverage and accuracy can be achieved on this task compared to the gold standard; (b) how ...
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Crowdsourced Hedge Term Disambiguation
... We address the issue of acquiring quality an- notations of hedging words and phrases, lin- guistic phenomenona in which words, sounds, or other constructions are used to express am- biguity or uncertainty. Due to the ...
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Similarity based Word Sense Disambiguation
... 4 The weight of a w o r d estimates its expected contribution to the disambiguation task and is a product of several factors: the frequency of the w o r d in the corpus; its frequency in[r] ...
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New Techniques for Disambiguation in Natural Language and Their Application to Biological Text
... The performance of the proposed methods, Naive Bayes classifier with six smoothing tech- niques, and the SNoW classifier are studied carefully on the gene/protein name disambiguation task. We consider the ...
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Amazon Mechanical Turk for Subjectivity Word Sense Disambiguation
... Amazon Mechanical Turk (MTurk) is a mar- ketplace for so-called “human intelligence tasks” (HITs), or tasks that are easy for hu- mans but currently difficult for automated pro- cesses. Providers upload tasks to MTurk ...
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Scaling to Very Very Large Corpora for Natural Language Disambiguation
... language disambiguation task, confusion set disambiguation, when trained on orders of magnitude more labeled data than has previously been ...
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The Disambiguation of Nominalizations
... interpretation task as a dis- ambiguation ...the disambiguation task and show that performance is increased by taking contextual features into ...
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Chinese Name Disambiguation Based on Adaptive Clustering with the Attribute Features
... evaluation task CLP2012 named entity recognition and disam- biguation in Chinese, a Chinese name disambigua- tion method based on adaptive clustering with the attribute features is proposed, which will resolve ...
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SenseSpotting: Never let your parallel data tie you to an old domain
... In the previous section, we observed that (with one exception) both Type-level and Token-level fea- tures are useful in our task (in some cases, essen- tial). In this section, we look at finer-grained fea- ture ...
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SemEval 2007 Task 11: English Lexical Sample Task via English Chinese Parallel Text
... We made use of parallel texts to gather train- ing and test examples for the English lexi- cal sample task. Two tracks were organized for our task. The first track used examples gathered from an LDC corpus, ...
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PP Attachment Disambiguation Boosted by a Gigantic Volume of Unambiguous Examples
... We acquire lexical preferences that are useful for PP-attachment disambiguation from a raw corpus. As such lexical preferences, cooccurrence statistics between the verb and the prepositional phrase or the noun and ...
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Combining Stochastic and Rule Based Methods for Disambiguation in Agglutinative Languages
... Combining Stochastic and Rule Based Methods for Disambiguation in Agglutinative Languages Combining Stochastic and Rule Based Methods for Disambiguation in Agglutinative Languages Ezeiza N , Alegria I[.] ...
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Interactive Instance based Evaluation of Knowledge Base Question Answering
... analysis task while a moderator was sitting near them and monitoring the ...the task in under 10 minutes and could point out at what stage an error has occurred for all input ...
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The Task 2 of CIPS SIGHAN 2012 Named Entity Recognition and Disambiguation in Chinese Bakeoff
... Named Entity Recognition and Disambiguation (NERD) is the task of detecting entity mentions from raw text and classifying each mention to its real world entity. NERD is a fundamental prob- lem in Natural ...
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