Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Extensive study on automatic verb sense disambiguation in czech
TSD'06 Proceedings of the 9th international conference on Text, Speech and Dialogue
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VALLEX is a linguistically annotated lexicon aiming at a description of syntactic information which is supposed to be useful for NLP. The lexicon contains roughly 2500 manually annotated Czech verbs with over 6000 valency frames (summer 2005). In this paper we introduce VALLEX and describe an experiment where VALLEX frames were assigned to 10,000 corpus instances of 100 Czech verbs – the pairwise inter-annotator agreement reaches 75%. The part of the data where three human annotators agreed were used for an automatic word sense disambiguation task, in which we achieved the precision of 78.5%.