Proceedings - Österreichische Gesellschaft für Artificial Intelligence

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Figure 1: Screenshot of the public Data Category Selection “Uby 2012“ in ISOCat, see http://www.isocat.org/interface/index.html. term determiner which is a possible value of the attribute partOfSpeech in UBY-LMF. There are 25 DCs in ISOCat that exactly match the term determiner. Another example is the term direct object that is sometimes used for specifying the accusative noun phrase argument of transitive verbs in German. In ISOCat, there are two different specifications of this term, one explicitly stating that this accusative noun phrase argument can become the clause subject in passivization (http://www.isocat.org/datcat/DC-1274), the other not mentioning passivization at all (http://www.isocat.org/datcat/DC-2263). We tried to select a DC with a meaning as close as possible to the intended meaning in UBY-LMF. When selecting a particular DC from a list of candidates, we followed two simple strategies: • We sorted the search results by Owner, i.e., by the person who created the DC, and preferred DCs which are owned by experts, either in the standardization community or in the linguistics community. • We preferred those DCs that had passed the ISOCat test for well-formedness. Sometimes, selecting an existing DC from ISOCat involved making compromises. For instance, the attribute value taxonomic of the attribute relType of the SenseRelation class links to the ISOCat DC taxonomy (http://www.isocat.org/rest/dc/4039) which has a narrower meaning than the meaning intended in UBY-LMF: While taxonomic in UBY-LMF denotes a type of sense relation that defines a taxonomy in a general sense, covering 500 <strong>Proceedings</strong> of KONVENS 2012 (SFLR 2012 workshop), Vienna, September 21, 2012
all kinds of lexemes, (see Cruse (1986)), the DC 4039, taxonomy, is restricted to controlled vocabulary terms organized in a taxonomy. Note that many attributes or attribute values in UBY-LMF refer to ISOCat DCs with a different (so-called admitted) name. This is explicitly supported by ISOCat, because each DC definition may optionally contain Data Element Name Sections in order to record other names for the DC as used in different sources, such as a given database, format or application. In this manner, the number of parallel DCs in ISOCat with equivalent meaning can be limited. We left the specification of Data Element Name Sections in the newly created DCs (holding a deviating UBY name) to future work. Semantic Drift As ISOCat is a collaboratively constructed and thus dynamically evolving repository, DCs that are not standardized yet could eventually change their meaning over time, e.g., they might be further fleshed out and specified in more detail. Since the public release of UBY in March 2012, we have already encountered such a case of semantic drift for the DC verbFormMood (see http://www.isocat.org/rest/dc/1427) which we selected as a description of the attribute verbForm attached to the SyntacticCategory class in the Syntax part of UBY-LMF. The DC verbFormMood has been changed after March 2012 (according to the change log, this DC was changed on 2012-06-09) and is no longer similar enough to the intended meaning. Therefore, we will create a new DC which specifies verbForm as a property of verb phrase complements in the context of subcategorization. 4.3 UBY-LMF: Creating new ISOCat DCs The majority of attributes and values in UBY- LMF refer to already existing ISOCat DCs. Yet, we had to create 38 new DCs in ISOCat, as particular definitions were missing. We decided to create new DCs in those domains where much standardization work has already been done or large sources of linguistic expert knowledge are available. In particular, these are the domains lexical syntax (related to subcategorization), derivational morphology, and frame semantic information. We used the following expert-based sources as references for newly created DCs: • the EAGLES synopsis on morphosyntactic phenomena 10 (Calzolari and Monachini, 1996), as well as the EAGLES recommendations on subcategorization 11 have been used to identify DCs relevant for lexical syntax • traditional grammars such as the English grammar by Quirk (1980) • a Web-based encyclopedia of linguistic terms, collaboratively built by linguists, see http://www.glottopedia.de • the detailed documentation of the FrameNet resource (Ruppenhofer et al., 2010) Fifteen of the newly created DCs are required for representing subcategorization frames in UBY- LMF. Most of these DCs are simple DCs that are linked to attribute values in UBY-LMF. The corresponding DCs were either missing in ISOCat or there were only DCs with a related, but not sufficiently similar meaning. For instance, we created a DC for to-infinitive complements as in He tried to address all questions.. While both infinitive and infinitiveParticle are present in ISOCat, all available definitions of infinitive do not explicitly exclude the presence of a particle, neither http://www.isocat.org/datcat/DC-1312 nor http://www.isocat.org/datcat/DC-2753. What is required, however, for the specification of verbal complements are individual DCs for bare infinitives used without particle and for infinitives used with particle (i.e., to in English). Ten newly created DCs are necessary to represent FrameNet in LMF and primarily describe specific properties of frame-semantic frames, e.g., coreness, incorporated semantic argument or transparent meaning. 4.4 UBY-LMF: Limitations of semantic interoperability The semantic interoperability of a UBY-LMF compliant resource is naturally limited to those domains within UBY-LMF where attributes and 10 http://www.ilc.cnr.it/EAGLES96/morphsyn/ 11 http://www.ilc.cnr.it/EAGLES96/synlex/ 501 <strong>Proceedings</strong> 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
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3 Theoretical Background Let us now
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are sensible to semantic properties
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Cançado, Márcia and Amaral, Luana
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morphological tagger for Russian la
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Page 451 and 452: Verb class same frame different fra
Page 453 and 454: Construction Grammar are introduced
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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 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: can register and create DCs. Users
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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