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From Stance to Concern: Adaptation of Propositional Analysis to New Tasks and Domains ...
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Detecting Asks in SE attacks: Impact of Linguistic and Structural Knowledge ...
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Adaptation of a Lexical Organization for Social Engineering Detection and Response Generation ...
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Measuring Degrees of Semantic Opposition ...
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Abstract:
Knowing the degree of semantic contrast, or oppositeness, between words has widespread application in natural language processing, including machine translation, and information retrieval. Manually-created lexicons focus on strict opposites, such as antonyms, and have limited coverage. On the other hand, only a few automatic approaches have been proposed, and none have been comprehensively evaluated. Even though oppositeness may seem to be a simple and fairly intuitive idea at first glance, any deeper analysis quickly reveals that it is in fact a complex and heterogeneous phenomenon. In this paper we present a large crowdsourcing experiment to determine the amount of human agreement on the concept of oppositeness and its different kinds. In the process, we flesh out key features of different kinds of opposites and also determine their relative prevalence. We then present an automatic and empirical measure of lexical contrast that combines corpus statistics with the structure of a published thesaurus. Using ...
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Keyword:
affixes; antonymy; closest-to-opposite questions; crowdsourcing; distributional hypothesis; kinds of opposites; lexical contrast; thesaurus structure
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URL: https://nrc-publications.canada.ca/eng/view/object/?id=9994b07b-738c-4bcc-b884-98b4560e7566 https://dx.doi.org/10.4224/19040608
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Citation Handling for Improved Summarization of Scientific Documents
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Measuring Variability in Sentence Ordering for News Summarization
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Challenges in Building an Arabic-English GHMT System with SMT Components
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Construction of a Chinese-English Verb Lexicon for Embedded Machine Translation in Cross-Language Information Retrieval
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Domain-Specific Term-List Expansion Using Existing Linguistic Resources
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Constraints on the Generation of Tense, Aspect, and Connecting Words from Temporal Expressions
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Handling Translation Divergences: Combining Statistical and Symbolic Techniques in Generation-Heavy Machine Translation
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Handling Translation Divergences in Generation-Heavy Hybrid Machine Translation
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Efficient Language Independent Generation from Lexical Conceptual Structures
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Lexical Resource Integration across the Syntax-Semantics Interface
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Mapping Lexical Entries in a Verbs Database to WordNet Senses
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Large Scale Language Independent Generation Using Thematic Hierarchies
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