The nature of statistical learning theory
The nature of statistical learning theory
The combinatory morphemic lexicon
Computational Linguistics
Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Three generative, lexicalised models for statistical parsing
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Statistical decision-tree models for parsing
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
A new statistical parser based on bigram lexical dependencies
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Three new probabilistic models for dependency parsing: an exploration
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Backward beam search algorithm for dependency analysis of Japanese
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
A statistical parser for Czech
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Probabilistic parsing for German using sister-head dependencies
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Is it harder to parse Chinese, or the Chinese Treebank?
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Towards history-based grammars: using richer models for probabilistic parsing
HLT '91 Proceedings of the workshop on Speech and Natural Language
Dependency Parsing with an Extended Finite-State Approach
Computational Linguistics
Two statistical parsing models applied to the Chinese Treebank
CLPW '00 Proceedings of the second workshop on Chinese language processing: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 12
Japanese dependency analysis using cascaded chunking
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Memory-Based Language Processing (Studies in Natural Language Processing)
Memory-Based Language Processing (Studies in Natural Language Processing)
Inductive Dependency Parsing (Text, Speech and Language Technology)
Inductive Dependency Parsing (Text, Speech and Language Technology)
Pseudo-projective dependency parsing
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Lexicalization in crosslinguistic probabilistic parsing: the case of French
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Learning morphological disambiguation rules for Turkish
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
CoNLL-X shared task on multilingual dependency parsing
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Experiments with a multilanguage non-projective dependency parser
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
LingPars, a linguistically inspired, language-independent machine learner for dependency treebanks
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Dependency parsing by inference over high-recall dependency predictions
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Projective dependency parsing with perceptron
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
A pipeline model for bottom-up dependency parsing
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Multi-lingual dependency parsing at NAIST
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Dependency parsing with reference to Slovene, Spanish and Swedish
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Vine parsing and minimum risk reranking for speed and precision
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Investigating multilingual dependency parsing
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Dependency parsing based on dynamic local optimization
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Multilingual dependency analysis with a two-stage discriminative parser
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Labeled pseudo-projective dependency parsing with support vector machines
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Multi-lingual dependency parsing with incremental integer linear programming
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Language independent probabilistic context-free parsing bolstered by machine learning
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Maximum spanning tree algorithm for non-projective labeled dependency parsing
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
The exploration of deterministic and efficient dependency parsing
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Dependency parsing as a classification problem
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Incrementality in deterministic dependency parsing
IncrementParsing '04 Proceedings of the Workshop on Incremental Parsing: Bringing Engineering and Cognition Together
A classifier-based parser with linear run-time complexity
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
ICCPOL'06 Proceedings of the 21st international conference on Computer Processing of Oriental Languages: beyond the orient: the research challenges ahead
Improving Arabic dependency parsing with lexical and inflectional morphological features
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
Two methods to incorporate local morphosyntactic features in Hindi dependency parsing
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
Application of different techniques to dependency parsing of Basque
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
On the role of morphosyntactic features in Hindi dependency parsing
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
Improving Arabic dependency parsing with form-based and functional morphological features
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
A Computational Analysis of Interaction Patterns in the Acquisition of Turkish
Research on Language and Computation
Information retrieval from turkish radiology reports without medical knowledge
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
One-step statistical parsing of hybrid dependency-constituency syntactic representations
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
Testing the effect of morphological disambiguation in dependency parsing of Basque
SPMRL '11 Proceedings of the Second Workshop on Statistical Parsing of Morphologically Rich Languages
Multiword expressions in statistical dependency parsing
SPMRL '11 Proceedings of the Second Workshop on Statistical Parsing of Morphologically Rich Languages
Getting more from morphology in multilingual dependency parsing
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Morphological and syntactic case in statistical dependency parsing
Computational Linguistics
Dependency parsing of modern standard arabic with lexical and inflectional features
Computational Linguistics
Turkish constituent chunking with morphological and contextual features
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Hi-index | 0.00 |
The suitability of different parsing methods for different languages is an important topic in syntactic parsing. Especially lesser-studied languages, typologically different from the languages for which methods have originally been developed, pose interesting challenges in this respect. This article presents an investigation of data-driven dependency parsing of Turkish, an agglutinative, free constituent order language that can be seen as the representative of a wider class of languages of similar type. Our investigations show that morphological structure plays an essential role in finding syntactic relations in such a language. In particular, we show that employing sublexical units called inflectional groups, rather than word forms, as the basic parsing units improves parsing accuracy. We test our claim on two different parsing methods, one based on a probabilistic model with beam search and the other based on discriminative classifiers and a deterministic parsing strategy, and show that the usefulness of sublexical units holds regardless of the parsing method. We examine the impact of morphological and lexical information in detail and show that, properly used, this kind of information can improve parsing accuracy substantially. Applying the techniques presented in this article, we achieve the highest reported accuracy for parsing the Turkish Treebank.