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The universal parser architecture for knowledge-based machine translation
, 1987
"... Machine translation should be semanticalty-accurate, linguistically-principled, user-interactive, and extensible to multiple languages and domains. This paper presents the universal parser architecture that strives to meet these objectives. In essence, linguistic knowledge bases (syntactic, semantic ..."
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Cited by 13 (2 self)
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Machine translation should be semanticalty-accurate, linguistically-principled, user-interactive, and extensible to multiple languages and domains. This paper presents the universal parser architecture that strives to meet these objectives. In essence, linguistic knowledge bases (syntactic
Machine translation supported by terminological information
- PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON THEORETICAL AND METHODOLOGICAL ISSUES IN MACHINE TRANSLATION
, 1993
"... It is well-known that natural language (NL) is highly complex and ambiguous, and designing a system in the sense of 'large scale engineering' rather than in the sense of so-called 'runnable specifications', i.e. computational solutions to pre-selected NL problem areas, which coul ..."
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Cited by 4 (1 self)
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little attention in computational linguistics; an unfortunate situation given that natural language processing (NLP) systems seem to be most successful when applied to specialised domains. In this paper we present an approach that integrates an instance of computational terminology into a constraint
Linguistic Evaluation of Support Verb Constructions by OpenLogos and Google Translate
"... This paper presents a systematic human evaluation of translations of English support verb constructions produced by a rule-based ma-chine translation (RBMT) system (OpenLogos) and a statistical machine translation (SMT) system (Google Translate) for five languages: French, German, Italian, Portugues ..."
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Cited by 1 (0 self)
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, Portuguese and Spanish. We classify support verb constructions by means of their syntactic structure and semantic behavior and present a qualitative analysis of their translation errors. The study aims to verify how machine translation (MT) systems translate fine-grained linguistic phenomena, and how well
Not All Neural Embeddings are Born Equal
"... Neural language models learn word representations that capture rich linguistic and conceptual information. Here we investigate the embeddings learned by neural machine translation models. We show that translation-based embeddings outper-form those learned by cutting-edge monolingual models at single ..."
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Neural language models learn word representations that capture rich linguistic and conceptual information. Here we investigate the embeddings learned by neural machine translation models. We show that translation-based embeddings outper-form those learned by cutting-edge monolingual models
unknown title
"... Machine translation should be semanticalty-accurate, linguisticallyprincipled, user-interactive, and extensible to multiple languages and domains. This paper presents the universal parser architecture that strives to meet these objectives. In essence, linguistic knowledge bases (syntactic, semantic, ..."
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Machine translation should be semanticalty-accurate, linguisticallyprincipled, user-interactive, and extensible to multiple languages and domains. This paper presents the universal parser architecture that strives to meet these objectives. In essence, linguistic knowledge bases (syntactic, semantic
Transfer and Architecture: Views from Chart Parsing
, 1994
"... The objective of this report is to describe the embedding of a transfer module within an alternative architectural approach for machine translation of spontaneous spoken language. The approach is cognitively oriented, i.e. it adapts some of the assumed properties of human language comprehension and ..."
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Cited by 1 (1 self)
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The objective of this report is to describe the embedding of a transfer module within an alternative architectural approach for machine translation of spontaneous spoken language. The approach is cognitively oriented, i.e. it adapts some of the assumed properties of human language comprehension
Semi-Automatic UNL Dictionary Generation using WordNet.PT
"... The increase of Internet users all over the world and the subsequent growth of available multilingual information on the Web have brought new challenges to machine translation systems. The Universal Networking Language (UNL) is a meta-language developed for conveying linguistic expressions in order ..."
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Cited by 1 (0 self)
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The increase of Internet users all over the world and the subsequent growth of available multilingual information on the Web have brought new challenges to machine translation systems. The Universal Networking Language (UNL) is a meta-language developed for conveying linguistic expressions in order
IDO DAGAN – RESEARCH STATEMENT
, 2002
"... Linguistics) deals with two fundamental goals. The first is developing generic algorithms and computational models for analyzing the full range of human language behavior. The second goal, which relies largely on the first, is developing the needed algorithms for robust textbased applications, such ..."
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and conferences. At the same time, researchers are gradually integrating learning with linguistic models, so that empirical analysis refers to deeper language phenomena. The remainder of this document illustrates major lines of my research and its current focus and plans.
Models in science’,
- The Stanford Encyclopedia of Philosophy. The Metaphysics Research Lab,
, 2008
"... Models are of central importance in many scientific contexts. The centrality of models such as the billiard ball model of a gas, the Bohr model of the atom, the MIT bag model of the nucleon, the Gaussian-chain model of a polymer, the Lorenz model of the atmosphere, the Lotka-Volterra model of preda ..."
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Cited by 21 (1 self)
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. Converting knowledge about the model into knowledge about the target Once we have knowledge about the model, this knowledge has to be 'translated' into knowledge about the target system. It is at this point that the representational function of models becomes important again. Models can instruct us
Results 1 - 10
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