Towards a general theory of action and time
Artificial Intelligence
The acquisition of syntactic knowledge
The acquisition of syntactic knowledge
Temporal ontology and temporal reference
Computational Linguistics - Special issue on tense and aspect
A computational model of the semantics of tense and aspect
Computational Linguistics - Special issue on tense and aspect
Building a lexicon for machine translation: use of corpora for aspectual classification of verbs
Building a lexicon for machine translation: use of corpora for aspectual classification of verbs
Maintaining knowledge about temporal intervals
Communications of the ACM
A Two-Level Knowledge Representation for Machine Translation: Lexical Semantics and Tense/Aspect
Proceedings of the First SIGLEX Workshop on Lexical Semantics and Knowledge Representation
Aspectual Requirements of Temporal Connectives: Evidence for a Two-Level Approach to Semantics
Proceedings of the First SIGLEX Workshop on Lexical Semantics and Knowledge Representation
Principle-Based Parsing for Machine Translation
Principle-Based Parsing for Machine Translation
Tense, aspect and the cognitive representation of time
ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
Solving thematic divergences in machine translation
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Machine translation divergences: a formal description and proposed solution
Computational Linguistics
Automatic extraction of aspectual information from a monolingual corpus
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
Parameterization of the interlingua in machine translation
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Information Processing and Management: an International Journal
Selecting tense aspect and connecting words in language generation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
N-gram-based tense models for statistical machine translation
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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This paper discusses how a two-level knowledge representation model for machine translation integrates aspectual information with lexical-semantic information by means of parameterization. The integration of aspect with lexical-semantics is especially critical in machine translation because of the lexical selection and aspectual realization processes that operate during the production of the target-language sentence: there are often a large number of lexical and aspectual possibilities to choose from in the production of a sentence from a lexical semantic representation. Aspectual information from the source-language sentence constrains the choice of target-language terms. In turn, the target-language terms limit the possibilities for generation of aspect. Thus, there is a two-way communication channel between the two processes. This paper will show that the selection/realization processes may be parameterized so that they operate uniformly across more than one language and it will describe how the parameter-based approach is currently being used as the basis for extraction of aspectual information from corpora.