A simple rule-based part of speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
Transformation-based learning in the fast lane
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Non-projective dependency parsing using spanning tree algorithms
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Transformation-based tectogrammatical dependency analysis of English
TSD'07 Proceedings of the 10th international conference on Text, speech and dialogue
Fuzzy ILP Classification of web reports after linguistic text mining
Information Processing and Management: an International Journal
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There are several tools that support manual annotation of data at the Tectogrammatical Layer as it is defined in the Prague Dependency Treebank Using transformation-based learning, we have developed a tool which outperforms the combination of existing tools for pre-annotation of the tectogrammatical structure by 29% (measured as a relative error reduction) and for the deep functor (i.e., the semantic function) by 47% Moreover, using machine-learning technique makes our tool almost independent of the language being processed This paper gives details of the algorithm and the tool.