Bladier, Tatiana

Kallmeyer, Laura

van Cranenburgh, Andreas

English

Proceedings - University of Groningen

   University of GroningenExtraction of LTAG-based supertags from the French TreebankBladier, Tatiana; van Cranenburgh, Andreas; Kallmeyer, LauraIMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite fromit. Please check the document version below.Document VersionPublisher's PDF, also known as Version of recordPublication date:2018Link to publication in University of Groningen/UMCG research databaseCitation for published version (APA):Bladier, T., van Cranenburgh, A., & Kallmeyer, L. (2018). Extraction of LTAG-based supertags from theFrench Treebank: challenges and possible solutions.CopyrightOther than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of theauthor(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).The publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license.More information can be found on the University of Groningen website: https://www.rug.nl/library/open-access/self-archiving-pure/taverne-amendment.Take-down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons thenumber of authors shown on this cover page is limited to 10 maximum.Download date: 12-10-2022Extraction of LTAG-based supertags from the French Treebank:challenges and possible solutionsTatiana Bladier1, Andreas van Cranenburgh2, Laura Kallmeyer11Heinrich Heine University Düsseldorf2 University of Groningen{bladier, kallmeyer}@phil.hhu.de, a.w.van.cranenburgh@rug.nlIntroduction. In the present paper we present an approach to automatically extract Lexicalized TreeAdjoining Grammars [LTAG; 6] from the French Treebank [FTB; 1], which can be used for the LTAGsupertagging and parsing. We discuss the challenges encountered while extracting the grammars, proposeour solutions, and evaluate our French LTAG grammars on the supertagging task.LTAG is a linguistically and psychologically motivated grammar formalism. Productions in LTAGs sup-port an extended domain of locality, which allows them to express linguistic generalizations that are notcaptured by typical statistical parsers based on context-free grammars or dependency parsing. Parsing withLTAGs can be facilitated through the intermediate step of supertagging—a task of assigning a sequenceof LTAG tree templates (supertags) for a given sentence. Supertagging is referred to as being “almostparsing”, since it takes much of syntactic disambiguation before applying a costly parsing algorithm [3].Several supertagging approaches have been proposed for LTAGs [7, 2], with the most recent advancesincluding approaches based on Recurrent Neural Networks (RNN) [9]. While supertagging experimentswere reported for English [3, 9] and German [12], to our best knowledge, no research was reported onsupertagging with French LTAGs.Extraction of a feasible LTAG supertag lexicon. Neural supertagging with LTAGs is a sequence labelingproblem. Thus, the performance of the supertagger on the classification task strongly depends on the sizeof the supertag lexicon—in case of a too large number of supertags, the supertagging system has to makea choice between a bigger number of options and thus suffers a drop of performance. Recent research onsupertagging with automatically induced LTAG grammars for English and German [9, 12] shows that themanageable size of a supertag lexicon contains around 4000 distinct supertags with roughly a half of thesupertags appearing only once (see Table 1).LTAG Induction. We used the French Treebank for the grammar extraction due to its being the currentlylargest available and the most widely used resource for the French language. In order to extract an LTAGfrom the FTB, we applied the heuristic top-down procedure described by Xia [13]. For facilitation ofthe LTAG induction we carried out pre-processing steps described in Candito et al. [4] and Crabbé andCandito [5] including extension of the original POS tag set in FTB from 13 to 26 POS tags, undoing mostmultiword expressions with regular syntactic patterns and raising some complements (e.g. raising the PPsof the VPinf constituents). We experimented with the following LTAGs for French: including 13 or 26POS tags, with or without compounds, including and excluding punctuation marks (see Table 2).Challenges while extracting supertags from FTB. A big number of flat multi-word expressions (MWEs)in FTB leads to a large number of rather infrequent distinct extracted supertags. About 14 % of the wordtokens in FTB belong to flat MWEs. After rewriting compounds with regular syntactic patterns, thenumber of MWEs is reduced to approximately 5 %. Extending the set of part-of-speech tags provided byFTB to more fine-grained 26 POS-tags theoretically helps the supertagger to better learn the dependenciesbetween the supertags, however, a bigger number of POS tags leads to a higher number of supertags, whichcauses a drop of performance.Left- and right-sister-adjunction. The tree structures in FTB are rather flat and allow any ordering ofarguments and modifiers. In order to preserve these original flat structures as far as possible we decidedagainst the traditional notion of adjunction in TAG which relies on nested structures and apply sister-adjunction; i.e., the root of a sister-adjoining tree can be attached as a daughter of any node of another treewith the same node label. Since a modifier can appear on the right or on the left side relative to the positionof the constituent head, we distinguish between right- and left-sister-adjoining trees—marked with * onthe left or the right side of the root label as shown in Figure 1.Evaluation and future work. We evaluated our extracted grammars on experiments with an implementedsupertagger similar to the one described in Kasai et al. [9] and Samih [10]. Our results show that theextracted grammars get comparable results with the data for English and German LTAG. In our futurework we plan to improve the supertagger and to use it for graph-based parsing. In particular, we aim atadapting the A*-based PARTAGE parser for LTAGs developed by Waszczuk [11] for parsing with extractedsupertags. We also intend to add deep syntactic features and information on semantic roles to the supertagsin order to test whether extracted LTAGs can be used for semantic role labeling.Parameters French German, reduced set German, full set English(this work) Kaeshammer [8] Kaeshammer [8] Kasai et al. [9]Supertags 5145 2516 3426 4727Supertags occur. once 2693 1123 1562 2165POS tags 13 53 53 36Sentences 21550 28879 50000 44168Avg. sentence length 31.34 17.51 17.71 appr. 20Supertagging accuracy 78.54 85.91 88.51 89.32Table 1: Comparison of LTAGs extracted from different treebanksExtracted French LTAG # supertags # supertags once Supertagging accuracy13 POS, undone comp. 5145 2693 78.5413 POS, with compounds 6847 3738 76.7826 POS, with compounds 5831 3008 74.8413 POS, undone comp., no punct. marks 5015 2557 74.44Table 2: Supertagging experiments with different LTAGs extracted from the FTB.NP-SUJ*DL’theVN*ADVnenotNP-SUJNactivitéactivityROOTSENTNP-SUJ↓ VNVPsuffitsuffice*SENTADVpas�negat.�=⇒ROOTSENTNP-SUJDL’theNactivitéactivityVNADVnenotVPsuffitsufficeADVpas�negat.�Figure 1: Left- and right-sister-adjunction for L’activité ne suffit pas (“The activity does not suffice”)References[1] Anne Abeillé, Lionel Clément, and François Toussenel. Building a treebank for French. In Treebanks, pages 165–187.Springer, 2003.[2] Jens Bäcker and Karin Harbusch. Hidden markov model-based supertagging in a user-initiative dialogue system. InProceedings of TAG+ 6, pages 269–278, 2002.[3] Srinivas Bangalore and Aravind K Joshi. Supertagging: An approach to almost parsing. Computational linguistics, 25(2):237–265, 1999.[4] Marie Candito, Benoı̂t Crabbé, and Pascal Denis. Statistical french dependency parsing: treebank conversion and firstresults. In Seventh International Conference on Language Resources and Evaluation-LREC 2010, pages 1840–1847.European Language Resources Association (ELRA), 2010.[5] Benoit Crabbé and Marie Candito. Expériences d’analyse syntaxique statistique du français. In 15ème conférence sur leTraitement Automatique des Langues Naturelles-TALN’08, pages pp–44, 2008.[6] Aravind K Joshi and Yves Schabes. Tree-adjoining grammars. In Handbook of formal languages, pages 69–123. Springer,1997.[7] Aravind K Joshi and Bangalore Srinivas. Disambiguation of super parts of speech (or supertags): Almost parsing. In Pro-ceedings of the 15th conference on Computational linguistics-Volume 1, pages 154–160. Association for ComputationalLinguistics, 1994.[8] Miriam Kaeshammer. A German treebank and lexicon for tree-adjoining grammars. PhD thesis, Masters thesis, Univer-sitat des Saarlandes, Saarlandes, Germany, 2012.[9] Jungo Kasai, Bob Frank, Tom McCoy, Owen Rambow, and Alexis Nasr. Tag parsing with neural networks and vector rep-resentations of supertags. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing,pages 1712–1722, 2017.[10] Younes Samih. Dialectal Arabic processing Using Deep Learning. PhD thesis, Düsseldorf, Germany, 2017. URLhttp://nbn-resolving.de/urn/resolver.pl?urn=urn:nbn:de:hbz:061-20180118-084822-9.[11] Jakub Waszczuk. Leveraging MWEs in practical TAG parsing: towards the best of the two world. PhD thesis, 2017.[12] Anika Westburg. Supertagging for german - an implementation based on tree adjoining grammars. Master’s thesis,Heinrich Heine University of Düsseldorf, 2016.[13] Fei Xia. Extracting tree adjoining grammars from bracketed corpora. In Proceedings of the 5th Natural LanguageProcessing Pacific Rim Symposium (NLPRS-99), pages 398–403, 1999.3

Extraction of LTAG-based supertags from the French Treebank:challenges and possible solutions

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Extraction of LTAG-based supertags from the French Treebank:challenges and possible solutions

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