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oughly described by the schema shown in Figure 5. A feature system declaration (fsdDecl) consists of one or more feature structure declarations (fsDecl). A feature structure declaration specifies the type of the structure and, optionally, one or more “base” types of which the type is a sub-type. In addition, a feature structure declaration consists of one or more feature declarations (fDecl), which specify the name of the features, the range of possible values and, optionally, a default value. Feature structure and type declarations. The following example sketches part of an FSD for the typed feature structure shown in Figure 2. The attribute baseTypes is used to declare that the type word is a subtype of the type sign. ... ... The example illustrates how to declare the range of possible feature values by means of the vRange construct. In fact, this is the only option if atomic values are represented by built-in elements such as symbol. In order to represent determiner, noun, verb etc. as members of the type hierarchy, they have to be treated as atomic feature structures along the following lines: ... ... Hence, the type hierarchy can be represented by an FSD document by declaring types as atomic feature structures together with the more general types from which the type in question inherits. 9 Feature structure constraints. One of the goals of the ISO standard is to allow for both, the feature structure declarations of typed feature structures in the style of HPSG (Pollard and Sag, 1994) and the representation of feature cooccurrence restrictions and defaults as employed in GPSG (Gazdar et al., 1985) and other untyped frameworks. While implicational constraints are also relevant for typed frameworks (cf., e.g., the principles of HPSG), they are fundamental to the untyped case. We will not go into detail here because the representation of such constraints is basically a question of how to represent logical expressions in general (which in turn is the topic of other initiatives such as RuleML). Examples adapted from Gazdar et al. (1985) can be found in Burnard and Bauman (2012, Sect. 18.11.4). 4 Discussion Is FSR/FSD more than an exchange format? The primary use case of the ISO 24610 standard is the exchange of feature structure data between applications. The question arises whether the XML representation of feature structures compliant with FSR is not only useful for exchanging data but also as a data format for application programming. In other words, can the XML representation serve as the native data format of an application? The appropriate answer is a qualified yes. On the one hand, existing XML technology (XML query languages, native XML databases) provides a powerful environment for working with FSR compliant data. On the other 9 There is a caveat here. The schema for fsDecl in ISO 24610-2 and TEI P5 apparently poses a problem for this strategy since it requires at least one fDecl child. Hence, strictly speaking, atomic feature structures cannot be declared. 492 Proceedings of KONVENS 2012 (SFLR 2012 workshop), Vienna, September 21, 2012
hand, checking the validity of FSR data directly on the basis of an FSD document is probably a tedious task, for which logic programming of one kind or another seems to be much better suited. Is there a need for software tools? As an application-oriented exchange format, the ISO standard does not aim at human readability. The question is, whether there is a need for viewing and editing or even validity checking of FSR compliant data. Given that an application system typically uses its own internal representation, which is part of an elaborate editing and programming environment, the answer could be negative. However, if the ISO standard is established as an export format, then a sufficiently powerful, freely available (open source) tool for browsing, editing and probably checking FSR/FSD data would be extremely helpful for accessing the data. Moreover, the existence of such a tool could boost the dissemination of the standard. Potential users would need to transform their data into the ISO format in order to use the tool. The ISO 24610 standard in context. How does the ISO 24610 standard relate to other standards for language resources developed by the ISO Sub-Committee TC 37/SC 4? According to the International Standard ISO 24612 ‘Linguistic annotation framework’ (LAF), the FSR standard plays a key role for any sort of annotation. LAF draws a clear-cut distinction between referential structure and annotation content structure and proposes that the latter be represented as feature structures compliant with FSR. It follows that the ISO 24610 standard is tied in with all standards related to linguistic content, be it morphosyntax, syntactic, or pragmatic content. Hence the standard contributes to the interoperability of the ISO standards for language resource management (Lee and Romary, 2010). Acknowledgments The writing of this paper has been supported by the Collaborative Research Center 991 ‘The Structure of Representations in Language, Cognition and Science’ funded by the German Research Foundation (DFG). References Lou Burnard and Syd Bauman, editors. 2012. TEI P5: Guidelines for Electronic Text Encoding and Interchange (Version 2.1.0). Text Encoding Initiative Consortium, Charlottesville, Virginia. [http://www.tei-c.org/Guidelines/P5/]. Bob Carpenter. 1992. The Logic of Typed Feature Structures. Cambridge University Press, Cambridge. Noam Chomsky and Morris Halle. 1968. The Sound Pattern of English. Harper & Row, New York. Gerald Gazdar, Ewan Klein, Geoffrey K. Pullum, and Ivan Sag. 1985. Generalized Phrase Structure Grammar. Blackwell, Oxford. ISO 24610-1. Language resource management - Feature structures - Part 1: Feature structure representation. Publication date: 2006-04. ISO 24610-2. Language resource management - Feature structures - Part 1: Feature system declaration. Publication date: 2011-10. ISO 24612. Language resource management - Linguistic annotation framework (LAF). Publication date: 2012-06. D. Terence Langendoen and Gery F. Simons. 1995. A rationale for the TEI recommendations for featurestructure markup. Computers and the Humanities, 29:191–209. Kiyong Lee and Laurent Romary. 2010. Towards interoperability of ISO standards for language resource management. In Proceedings of the Second International Conference on Global Interoperability for Language Resources, pages 95–103, Hong Kong. City University of Hong Kong. Kiyong Lee, Lou Burnard, Laurent Romary, Eric de la Clergerie Thierry Declerck, Syd Bauman, Harry Bunt, Lionel Clément Tomaz Erjavec, Azim Roussanaly, and Claude Roux. 2004. Towards an international standard on feature structures representation. In Proceedings of LREC 2004, pages 373–376, Lisbon, Portugal. Universidade Nova de Lisboa. Carl J. Pollard and Ivan A. Sag. 1994. Head-Driven Phrase Structure Grammar. University of Chicago Press, Chicago. Erik T. Ray. 2003. Learning XML. O’Reilly, Sebastopol, CA. Eric van der Vlist. 2003. RELAX NG. O’Reilly, Sebastopol, CA. Andreas Witt, Georg Rehm, Erhard Hinrichs, Timm Lehmberg, and Jens Stegmann. 2009. SusTEInability of linguistic resources through feature structures. Literary and Linguistic Computing, 24(3):363–372. 493 Proceedings of KONVENS 2012 (SFLR 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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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
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References Ahmad Abdulkader and Mat
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cision, recall, and F1. Section 4 d
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not corrected corrected p P R F1 P
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From Semi-Automatic to Automatic Af
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Figure 2: ER-Diagramm of the Morphi
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Figure 4: Morphilizer’s implement
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Figure 6: Architecture of Morphorm
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References Harald R. Baayen, R. Pie
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edition has been adopted. This is d
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marginalia, emendations or punctuat
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Word Lemma Class Subclass Type Tens
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Figure 3. Sample screenshot of comp
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KONVENS 2012 LexSem 2012: Workshop
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English) closely and discusses the
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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 and 460: Framenet++, VR dnr 2010-6013), by t
Page 461 and 462: Källström and Inger Lindberg, edi
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: ement, while the interpretation as
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
Page 511 and 512: Two multi-layer annotated corpora r
Page 513 and 514: As audio data is not directly store
Page 515 and 516: Jörg Mayer. 1995. Transcription of
Page 517 and 518: Towards standardized lexical semant
Page 519: Getting involved into language reso
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