Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
On the structural complexity of natural language sentences
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Reranking and self-training for parser adaptation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Syntactic complexity measures for detecting mild cognitive impairment
BioNLP '07 Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing
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
Multilingual dependency analysis with a two-stage discriminative parser
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Sample selection for statistical parsers: cognitively driven algorithms and evaluation measures
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
Automatic selection of high quality parses created by a fully unsupervised parser
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
When is self-training effective for parsing?
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Detecting parser errors using web-based semantic filters
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Distributed language modeling for N-best list re-ranking
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Automatic prediction of parser accuracy
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Improved fully unsupervised parsing with zoomed learning
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Empirical methods in natural language generation
Legal language and legal knowledge management applications
Semantic Processing of Legal Texts
ReliAble dependency arc recognition
Expert Systems with Applications: An International Journal
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In this paper we present ULISSE, an unsupervised linguistically--driven algorithm to select reliable parses from the output of a dependency parser. Different experiments were devised to show that the algorithm is robust enough to deal with the output of different parsers and with different languages, as well as to be used across different domains. In all cases, ULISSE appears to outperform the baseline algorithms.