Proceedings - Österreichische Gesellschaft für Artificial Intelligence

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Charles Fillmore, Paul Kay, and Mary Catherine O’Connor. 1988. Regularity and idiomaticity in grammatical constructions: the case of let alone. Language, 64:501–538. Charles Fillmore, Russell Lee Goldman, and Russell Rhodes. to appear. The FrameNet constructicon. In Hans Boas and Ivan Sag, editors, Sign-Based Construction Grammar. CSLI, Stanford. Charles Fillmore. 1982. Frame semantics. In Linguistics in the Morning Calm, pages 111–137. Hanshin Publishing Co, Seoul. Charles Fillmore. 2008. Border conflicts: FrameNet meets Construction Grammar. In Elisenda Bernal and Janet DeCesaris, editors, Proceedings of the XIII EURALEX International Congress, pages 49– 68, Barcelona. Mirjam Fried. to appear. Construction grammar. In A. Alexiadou and T. Kiss, editors, Handbook of Syntax (2nd ed.). de Gruyter, Berlin. Phani Gadde, Karan Jindal, Samar Husain, Dipti Misra Sharma, and Rajeev Sangal. 2010. Improving data driven dependency parsing using clausal information. In HLT: The 2010 Conference of the NAACL, pages 657–660, Los Angeles. Adele Goldberg. 1995. Constructions. A Construction Grammar approach to argument structure. University of Chicago Press, Chicago & London. Harald Hammarström and Lars Borin. 2011. Unsupervised learning of morphology. Computational Linguistics, 37(2):309–350. Patrick Hanks. 2008. The lexicographical legacy of John Sinclair. International Jornal of Lexicography, 21:219–229. Karin Friberg Heppin. 2011. MedEval – a Swedish medical test collection with doctors and patients user groups. Journal of Biomedical Semantics. Daniel Hewlett and Paul Cohen. 2011. Word segmentation as general chunking. In Proceedings of CoNLL 2011, pages 39–47, Portland, Oregon. Ray Jackendoff. 1997. The Architecture of the Language Faculty. MIT Press, Cambridge, MA. Håkan Jansson. 2006. Har du ölat dig odödlig? En undersökning av resultativkonstruktioner i svenskan [‘Have you aled yourself immortal? A study of resultative constructions in Swedish’]. Technical report, Dept. of Swedish, University of Gothenburg. Sofie Johansson Kokkinakis and Ulrika Magnusson. 2011. Computer based quantitative methods applied to first and second language student writing. In Roger Källström and Inger Lindberg, editors, Young urban Swedish. Variation and change in multilingual settings, pages 105–124. University of Gothenburg, Dept. of Swedish. Richard Johansson. 2012. Non-atomic classification to improve a semantic role labeler for a lowresource language. In Proceedings of the First Joint Conference on Lexical and Computational Semantics, pages 95–99, Montréal. Lauri Karttunen, Jean-Pierre Chanod, Gregory Grefenstette, and Anne Schiller. 1996. Regular expressions for language engineering. Natural Language Engineering, 2(4):305–328. Adam Kilgarriff, Miloš Husák, Katy McAdam, Michael Rundell, and Pavel Rychlý. 2008. Gdex: Automatically finding good dictionary examples in a corpus. In Proceedings of the XIII EURALEX International Congress, pages 425–432, l’Institut Universitari de Lingüística Aplicada (IULA) dela Universitat Pompeu Fabra. Dimitrios Kokkinakis. 2008. Semantic preprocessing for complexity reduction in parsing medical texts. In Proceedings of the 21th Conference on the European Federation for Medical Informatics (MIE 2008). Dimitrios Kokkinakis. 2012. The Journal of the Swedish Medical Association – a corpus resource for biomedical text mining in Swedish. In The Third Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM), an LREC Workshop, Istanbul. Ronald Langacker. 1991. Foundations of Cognitive Grammar. Volume II: Descriptive application. Stanford University Press, Stanford, CA. Benjamin Lyngfelt and Markus Forsberg. 2012. Ett svenskt konstruktikon. Utgångspunkter och preliminära ramar [‘A Swedish constructicon. Points of departure and preliminary guidelines’]. Technical report, Dept. of Swedish, University of Gothenburg. Benjamin Lyngfelt. 2007. Mellan polerna. Reflexivoch deponenskonstruktioner i svenskan [‘Between the poles. Reflexive and deponent constructions in Swedish’]. Språk och stil NF, 17:86–134. Daniela Oelke, Dimitrios Kokkinakis, and Mats Malm. 2012. Advanced visual analytics methods for literature analysis. In Proceedings of LaTECH 2012. Pavel Pecina. 2010. Lexical association measures and collocation extraction. Language Resources and Evaluation, 44:137–158. Jussi Piitulainen. 2010. Explorations in the distributional and semantic similarity of words. University of Helsinki. Carl Pollard and Ivan Sag. 1994. Head-Driven Phrase Structure Grammar. University of Chicago Press, Chicago & London. Julia Prentice and Emma Sköldberg. 2011. Figurative word combinations in texts written by adolescents in multilingual school environments. In Roger 460 Proceedings of KONVENS 2012 (LexSem 2012 workshop), Vienna, September 21, 2012
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11 th Conference on Natural Languag
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Table of Contents Main conference P
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Comparing variety corpora with vis-
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LexSem 2012: Workshop on Recent Dev
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KONVENS 2012 The 11 th Conference o
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Organizers: Jeremy Jancsary (ÖGAI/
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Ines Rehbein (Potsdam University) M
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Integrating viewpoints into newspap
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Phonetically aided syntactic parsin
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The Statistical Approach to Natural
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Data-driven Knowledge Extraction fo
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4 The Different Relations Types In
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Relation Type #Patterns Examples Su
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Suits-to Served-with Substituted-by
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References Timothy Chklovski and Pa
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1.2 Problem Definitions In a MRA, t
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oot person organisation product ...
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Group Organis. Persons Products all
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Method α α+β α+γ all SentiWS 0
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A Supervised POS Tagger for Written
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Our tagset mixes and matches tags a
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ecause the enclitic pronoun is an i
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stochastic rules as opposed to larg
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Kevin Duh, and Katrin Kirchhoff. 20
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forms, and that existentials can be
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Pseudo Verb Punctuation PNC
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NLP Workflow for On-line Definition
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nological phrases on the basis of p
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Figure 2: A screenshot of the entir
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When analyzing the evaluation sets
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Projecting Semantic Roles via Tai M
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quent prediction, return it (iii) i
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for the B/T/FT settings. This is pr
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ut it is implied by Table 3 and Fig
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References Wanxiang Che, Zhenghua L
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Our ultimate goal is to develop com
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ADORNING CAUSE_FLUIDIC_MOTION COTHE
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English nouns, verbs, adjectives, a
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considerably worse than FrameNet. T
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Extraction. In Proceedings of the 1
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lexicon from a document-derived voc
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Initialize hypernym set H to contai
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ulary distance. Let d(a, b) denote
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the reduced lexicon (243) was neare
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Adding nominal spice to SALSA - fra
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SALSA verbs nouns 0 FE 0 2 1 FE 68
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gen, which in one of its meanings i
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In the next section we describe how
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Acknowledgments This work was funde
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most commonly used (Turney and Pant
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anteed because the forward feature
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5 000 feat ICA50 SVD50 SENNA Semcat
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words bicycle and tricycle go with
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of the Twelfth European Conference
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incorporate the context information
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those candidate phrases that are an
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5.2 Evaluation Metrics for WPD The
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Runs F-measures α=0.5 α=0.2 Pur.
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Evaluations (SemEval-2007), June (2
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2 Related Work The majority of pape
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and Roth, 2009; Lin and Wu, 2009).
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Features Dev Test CoNLL-2003 w 0 +
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Feature Dev Test Test+ — 93.78 91
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the Joint Conference of the 47th An
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tion. It was first included as a sp
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indicates the presence of the ellip
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[Armada britainiarrak] [Ipar Irland
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Información, (JOTRI 2003), pages 1
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Phonetically aided Syntactic Parsin
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mar network or PCFG. Grammar networ
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phonetic confusion that has the con
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in confusion in the network. This i
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Linguistic analyses of the LAST MIN
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Table 1: Comparison between corpora
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Table 2: Most frequent POS patterns
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Table 3: A problematic dialog situa
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6 Summary We have presented the cur
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S-restricted monotone alignments St
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s k n i i: f phh ohehnh ih xh s k n
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Dataset µ G µ P P [G>15] P [P >15
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Perplexity H(L | P ) 2PKE-Uni 7.002
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(1, 1) (2, 1) (3, 1) (4, 1) (1, 2)
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Use of linguistic features for impr
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whereas English has a verb-initial
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Accuracy of Accuracy of Accuracy of
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English Persian Train: Sentences 30
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to compensate for sparsity of paral
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Name # Documents # Tokens # Lemmas
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Figure 1: Precision-Recall graphs c
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A Multi-level Annotation Model for
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and sentence level with the aim of
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(Schmid, 1995; Schiller et al., 199
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EI EII Tag AKR MARK Typography ITER
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References Saima Aman and Stan Szpa
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Robust processing of noisy web-coll
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1. first strip of the papery skin o
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References Jon Chamberlain, Massimo
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ments between its LSRs. Additionall
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Figure 3: In the sense comparison v
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Using Information Retrieval Technol
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against every tree. Others avoid th
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A 0.780715 NN Figure 4: A sp
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# #Documents Index Size 1 29,704 1.
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References P. Bański, C. Belica, H
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(2012), in their corpus study of va
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DET NSUBJ ADV OBJA AMOD Seine Tante
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A Computational Semantic Analysis o
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(6) a. Is Spain very large? b. Is B
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References Alan C. Bale. 2008. A Un
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219 Proceedings of KONVENS 2012 (Ma
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221 Proceedings of KONVENS 2012 (Ma
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Using subcategorization frames to i
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5.2 Word clustering based on the Le
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erage of english grammars. In Proce
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cases not disambiguated using langu
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Not surprisingly, the results show
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Automatic Identification of Languag
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Differences also appear at the synt
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Acknowledgments The authors express
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2 Related Work Previous work on POS
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The XY tag is used for all non-word
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Comparing Variety Corpora with Vis-
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INPUT variety corpus comparability
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References Andrea Abel and Stefanie
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Features Context features (token wi
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0.7 0.7 0.6 0.6 0.5 0.5 F-measure 0
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ties into fine-grained classes. In
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verbials (e.g., therefore, still).
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word raw freq. non conn. conn. (of
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Corpus-based Acquisition of German
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Events Objects IPrec CPrec IPrec CP
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References Marco Baroni, Silvia Ber
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Preface The present proceedings con
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Workshop Program Friday, September
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Unsupervised Sentiment Analysis wit
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pling (Geman and Geman, 1984) to es
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References Anders Björkelund, Bern
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Class # Events in % neutral 45’01
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3.1.1 Rules Let t 1..n be tokens of
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Human 6 System 6 Human 4 System 4 A
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Codebuch Akteursanalyse. rev. 2011.
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of our work in the whole applicatio
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3.4 Negation and graduation Valence
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local context. For instance, in une
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n’était pas très favorable au G
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Domain-specific variation of sentim
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query building blocks comments real
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References Monica Bednarek. 2006. E
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3 Basic Methodology of Annotation T
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(3) A. V případě jeho kandidatur
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4.3 Auxiliary data - Mall.cz We hav
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Overlap f-score Source 0.750 Polar
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A Phrase-Based Opinion List for the
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the Stuttgart-Tübingen Tagset (STT
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As for noun-based opinion phrases a
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More than half of the words and phr
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treebank. In Proceedings of the Wor
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Apart from these, we distinguish op
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close variants)”. In fact importa
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What is the Meaning of 5 *’s? An
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For each category, we follow (Const
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Positivity Term 2.87692577130 elske
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In recent years, the use of rating
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KONVENS 2012 LThist 2012: First Int
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Organisation Committee: Thierry Dec
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Workshop Program Friday, September
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Rule-Based Normalisation of Histori
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isation rules were applied to the i
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ments in the gold standard have bee
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cation in the contemporary SUC samp
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proach. References Maria Ågren, Ro
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2 Related Work There has been consi
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vided to ensure that they are norma
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alects, or even languages. Norma ca
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ization (rather than modernization)
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The Sketch Engine as infrastructure
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2.1 The Corpus of English Dialogues
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Other notable contrasts are that 17
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Evaluating a Post-editing Approach
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Figure 1: Example of a marriage lic
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all possible concatenations of indi
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Table 3: Post-editing results. Time
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okstaffua, bokstaffwa, bokstafwa, b
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Rule Cost v↔u 0.1 v↔w 0.1 u↔o
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graphic word boundaries and conside
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ation. Gulordava and Baroni (2011),
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ut adding a statistical measure to
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e.g. philosophical and political pr
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of the EACL 2009 Workshop on GEMS:
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Most of the research on genre class
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Precision Recall F 1 Unigrams 0.551
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The DTA ‘base format’: A TEI-Su
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Lib are complementary in the sense
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inline metadata solutions for edito
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ing. The fourth level contains an e
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the work package ‘Resources and T
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is mainly used with parallel corpor
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Corrections by the editor were omit
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Accuracy N % All Words 781/1000 78.
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$$ $$ $$ $$ $$ $$ $$ $$ $$ Figure 4
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Digitised Historical Text: Does it
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3 Related Work Previous research on
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5.1 End-of-line Soft Hyphen Deletio
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quite difficult to get an idea of h
Page 409 and 410: References Ahmad Abdulkader and Mat
Page 411 and 412: cision, recall, and F1. Section 4 d
Page 413 and 414: not corrected corrected p P R F1 P
Page 415 and 416: From Semi-Automatic to Automatic Af
Page 417 and 418: Figure 2: ER-Diagramm of the Morphi
Page 419 and 420: Figure 4: Morphilizer’s implement
Page 421 and 422: Figure 6: Architecture of Morphorm
Page 423 and 424: References Harald R. Baayen, R. Pie
Page 425 and 426: edition has been adopted. This is d
Page 427 and 428: marginalia, emendations or punctuat
Page 429 and 430: Word Lemma Class Subclass Type Tens
Page 431 and 432: Figure 3. Sample screenshot of comp
Page 433 and 434: KONVENS 2012 LexSem 2012: Workshop
Page 435 and 436: English) closely and discusses the
Page 437 and 438: Workshop Program Friday, September
Page 439 and 440: verbs were collected mostly from an
Page 441 and 442: 3 Theoretical Background Let us now
Page 443 and 444: are sensible to semantic properties
Page 445 and 446: Cançado, Márcia and Amaral, Luana
Page 447 and 448: morphological tagger for Russian la
Page 449 and 450: whom/which something is taken. (7cz
Page 451 and 452: Verb class same frame different fra
Page 453 and 454: Construction Grammar are introduced
Page 455 and 456: posed to Hon åker på måndag ‘S
Page 457 and 458: nitions of Agent, for example. Inst
Page 459: Framenet++, VR dnr 2010-6013), by t
Page 463 and 464: scoring function σ : W ×L×W →
Page 465 and 466: esults in the triple 〈heutige Son
Page 467 and 468: Unlexicalized links 7,833,635 n (i)
Page 469 and 470: The difference in accuracies betwee
Page 471 and 472: Towards high-accuracy bilingual phr
Page 473 and 474: over a set of candidate translation
Page 475 and 476: each soft restriction soft m set on
Page 477 and 478: (> 98% in scalable precision) and a
Page 479 and 480: References Colin Bannard and Chris
Page 481 and 482: Preface The need for automatically
Page 483 and 484: 15:50-16:15 Coffee break 16:15-16:4
Page 485 and 486: Standards for the technical infrast
Page 487 and 488: ⎡ ⎤ phrase CATEGORY np ⎡ ⎤
Page 489 and 490: The representation of the feature v
Page 491 and 492: ement, while the interpretation as
Page 493 and 494: hand, checking the validity of FSR
Page 495 and 496: Standardizing metadata descriptions
Page 497 and 498: 2 LMF and semantic interoperability
Page 499 and 500: can register and create DCs. Users
Page 501 and 502: all kinds of lexemes, (see Cruse (1
Page 503 and 504: constraints, because many aspects o
Page 505 and 506: Menzo Windhouwer. 2012. RELcat: a R
Page 507 and 508: the meeting in Rome as a starting p
Page 509 and 510: As these documents provide the refe
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Two multi-layer annotated corpora r
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As audio data is not directly store
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Jörg Mayer. 1995. Transcription of
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Towards standardized lexical semant
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Getting involved into language reso
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