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Verb Semantics and Lexical Selection

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arxiv cmp-lg/9406033 v3 pith:NN7JVF7Y submitted 1994-06-22 cmp-lg cs.CL

classification cmp-lgcs.CL
keywords selectionlexicalrepresentationrestrictionsschemesystemsverbverbs
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper will focus on the semantic representation of verbs in computer systems and its impact on lexical selection problems in machine translation (MT). Two groups of English and Chinese verbs are examined to show that lexical selection must be based on interpretation of the sentence as well as selection restrictions placed on the verb arguments. A novel representation scheme is suggested, and is compared to representations with selection restrictions used in transfer-based MT. We see our approach as closely aligned with knowledge-based MT approaches (KBMT), and as a separate component that could be incorporated into existing systems. Examples and experimental results will show that, using this scheme, inexact matches can achieve correct lexical selection.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

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    cs.CV 2025-08 unverdicted novelty 5.0 of 10

    Pretrained language models can select adversarial target labels more effectively than static lexical databases, particularly for semantically distant classes.

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  3. Multimodal Information Retrieval for Open World with Edit Distance Weak Supervision

    cs.IR 2025-06 conditional novelty 5.0 of 10

    FemmIR uses graph-edit-distance weak supervision over extracted object properties to rank multimodal retrieval results without any similarity labels or fine-tuning.

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