Grzegorz Chrupała

I am an assistant professor at the Tilburg Center for Cognition and Communication at the Tilburg University.

My research is focused on computational language learning. I am especially interested in cognitively-inspired models of language learning which illuminate language acquisition in humans while at the same time being useful for real-world text understanding applications.

I received my PhD from the School of Computing at Dublin City University. After that I worked as a researcher at the Spoken Language Systems group at Saarland University.

Publications

My Google scholar citation statistics

• Benjamin Roth, Grzegorz Chrupała, Michael Wiegand and Mittul Singh. 2012. Generalizing from Freebase and Patterns using Distant Supervision for Slot Filling. TAC 2012.
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• Afra Alishahi and Grzegorz Chrupała. 2012. Concurrent Acquisition of Word Meaning and Lexical Categories. EMNLP-CoNLL 2012.
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• Grzegorz Chrupała. 2012. Hierarchical clustering of word class distributions. NAACL-HLT 2012 Workshop on the Induction of Linguistic Structure.
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• Grzegorz Chrupała. 2012. Learning from evolving data streams: online triage of bug reports. EACL 2012.
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• Fang Xu, Stefan Kazalski, Grzegorz Chrupała, Benjamin Roth, Xujian Zhao, Michael Wiegand and Dietrich Klakow. 2011. Saarland University Spoken Language Systems Group at TAC KBP 2011. TAC 2011.
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• Grzegorz Chrupała. 2011. Efficient induction of probabilistic word classes with LDA. IJCNLP 2011.
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• Grzegorz Chrupała, Saeedeh Momtazi, Michael Wiegand, Stefan Kazalski, Fang Xu, Benjamin Roth, Alexandra Balahur and Dietrich Klakow. 2010. Saarland University Spoken Language Systems at the Slot Filling Task of TAC KBP 2010. TAC 2010.
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• Grzegorz Chrupała, Georgiana Dinu and Benjamin Roth. 2010. Enriched syntax-based meaning representation for answer extraction. SIGIR 2010 Workshop: Query Representation and Understanding
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• Grzegorz Chrupała and Afra Alishahi. 2010. Online Entropy-based Model of Lexical Category Acquisition. CoNLL 2010
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• Georgiana Dinu and Grzegorz Chrupała. 2010. Relatedness curves for acquiring paraphrases. ACL workshop GEMS 2010
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• Djamé Seddah, Grzegorz Chrupała, Özlem Çetinoğlu, Josef van Genabith and Marie Candito. 2010. Lemmatization and Lexicalized Statistical Parsing of Morphologically Rich Languages: the Case of French. NAACL SPMRL 2010 workshop
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• Grzegorz Chrupała and Dietrich Klakow. 2010. A Named Entity Labeler for German: exploiting Wikipedia and distributional clusters. LREC 2010
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• Afra Alishahi and Grzegorz Chrupała. 2009. Lexical Category Acquisition as an Incremental Process. PsychoCompLA-2009, Cogsci 2009
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• Michael Wiegand, Saeedeh Momtazi, Stefan Kazalski, Fang Xu, Grzegorz Chrupała and Dietrich Klakow. 2008. The Alyssa System at TAC QA 2008. TAC 2008
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• Grzegorz Chrupała, Georgiana Dinu and Josef van Genabith. 2008. Learning Morphology with Morfette. LREC 2008
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• Grzegorz Chrupała, Josef van Genabith. Using very large corpora to detect raising and control verbs. 2007. LFG07
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• Grzegorz Chrupała, Nicolas Stroppa, Josef van Genabith and Georgiana Dinu. 2007. Better Training for Function Labeling. RANLP 2007
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• Grzegorz Chrupała. 2006. Simple Data-Driven Context-Sensitive Lemmatization. SEPLN 2006
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• Grzegorz Chrupała and Josef van Genabith. 2006. Using Machine-Learning to Assign Function Labels to Parser Output for Spanish. COLING/ACL 2006
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• Grzegorz Chrupała and Josef van Genabith. 2006. Improving Treebank-Based Automatic LFG Induction for Spanish. LFG06
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• Xavier Carreras, Lluís Màrquez and Grzegorz Chrupała. 2004. Hierarchical Recognition of Propositional Arguments with Perceptrons. CoNLL-2004
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• Anthony Pym and Grzegorz Chrupała. 2005. The quantitative analysis of translation flows in the age of an international language. In Less Translated Languages, Albert Branchadell and Lovell Margaret West (eds.), 27-38. John Benjamins.
• Grzegorz Chrupała. 2003. Perl Scripting in Translation Project Management. In Across Languages and Cultures, Vol. 4, No. 1. (5 May 2003), pp. 109-132
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• Grzegorz Chrupała and Lidia Cámara. 2003. STAR Transit XV. In Entornos Informáticos de la Traducción Profesional, Gloria Corpas Pastor and María-José Varela Salinas, (eds.). Atrio, Granada.

Theses

• Grzegorz Chrupała. 2008. Towards a Machine-Learning Architecture for Lexical Functional Grammar Parsing. PhD dissertation, Dublin City University
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• Grzegorz Chrupała. 2003. Acquiring Verb Subcategorization from Spanish Corpora. DEA Thesis, University of Barcelona.
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• Grzegorz Chrupała. 1998. Bibliotheca in Fabula. The library motive in La biblioteca de Babel, The British Museum is Falling Down and Il nome della rosa. MA Thesis, University of Silesia.
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Software

Morfette is used by many people for morphological analysis. SemiNER is also popular for named entity tagging in German. Many of the other packages are quite specialized and are of interest mostly if you are a researcher working on similar problems as myself.

• Colada: implements online and minibatch word class class induction using Latent Dirichlet Allocation (LDA) with an Online Gibbs sampler.
• Ladybug: Online (incremental) triage of bug reports.
• LDA-wordclass: Soft word-class induction with Latent Dirichlet Allocation
• Lingo: Haskell NLP utilities
• Delta-H: Online entropy-based model of lexical category acquisition
• Sequor: a perceptron-based sequence labeler with a flexible feature template language. It is meant mainly for NLP applications such as Part of Speech tagging, syntactic chunking or Named Entity labeling. Includes:
  • SemiNER: a semi-supervised Named Entity labeler (with pre-trained models for German)
• Morfette: a tool for supervised learning of inflectional morphology. Comes with pre-trained models for Spanish and French.
• Funtag: Add grammatical function labels to constituency parse trees

Teaching

Invited Lectures and Tutorials

• Machine learning for NLP and MT

  (with Nicolas Stroppa, Google, Zurich)
  EU META Network of Excellence workshop, Barcelona, Spain, October 2010. Two-day intensive course for graduate students and META researchers covering a selection of machine learning techniques useful for NLP.

  • Introduction
  • Linear models for classification
  • Sequence Labeling 1
  • Sequence Labeling 2
  • Theoretical and practical issues
  • KNN, Kernels, Margins

• Introduction to classification and sequence labeling

  International Research Training Group - Annual Meeting, Irsee, Germany, June 2009. Half-day intensive tutorial for graduate students covering basic machine learning techniques useful for NLP. Slides

• Machine Learning for NLP

  Centre for Next-Generation Localisation, Dublin, Ireland, March 2009. Two-day intensive tutorial for graduate students covering a selection of machine learning techniques useful for NLP. Slides

Contact

Dr. Grzegorz Chrupała
Communication and Information Sciences
Tilburg University
PO Box 90153
5000 LE Tilburg
The Netherlands

Web: grzegorz.chrupala.me
Phone: +31 13 466 3106
Email: g.chrupala@uvt.nl