The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
(Meta-) evaluation of machine translation
StatMT '07 Proceedings of the Second Workshop on Statistical Machine Translation
Manual and automatic evaluation of machine translation between European languages
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
TectoMT: modular NLP framework
IceTAL'10 Proceedings of the 7th international conference on Advances in natural language processing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Structured vs. flat semantic role representations for machine translation evaluation
SSST-5 Proceedings of the Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation
A grain of salt for the WMT manual evaluation
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
Findings of the 2012 workshop on statistical machine translation
WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
DEPFIX: a system for automatic correction of Czech MT outputs
WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
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HMEANT (Lo and Wu, 2011a) is a manual MT evaluation technique that focuses on predicate-argument structure of the sentence. We relate HMEANT to an established linguistic theory, highlighting the possibilities of reusing existing knowledge and resources for interpreting and automating HMEANT. We apply HMEANT to a new language, Czech in particular, by evaluating a set of English-to-Czech MT systems. HMEANT proves to correlate with manual rankings at the sentence level better than a range of automatic metrics. However, the main contribution of this paper is the identification of several issues of HMEANT annotation and our proposal on how to resolve them.