TY - JOUR
T1 - Yet another application of inference in computational linguistics
AU - Bolshakov, Igor A.
AU - Gelbukh, Alexander
PY - 2001
Y1 - 2001
N2 - Texts in natural languages consist of words that are syntactically linked and semantically combinable-like political party, pay attention, or brick wall. Such semantically plausible combinations of two content words, which we hereafter refer to as collocations, are important knowledge in many areas of computational linguistics. We consider a lexical resource that provides such knowledge-a collocation database (CBD). Since such databases cannot be complete under any reasonable compilation procedure, we consider heuristic-based inference mechanisms that predict new plausible collocations based on the ones present in the CDB, with the help of a WordNet-like thesaurus. If an available collocation combines the entries A and B, and B is 'similar' to C, then A and C supposedly constitute a collocation of the same category. Also, we touch upon semantically induced morphological categories suiting for such inferences. Several heuristics for filtering out wrong hypotheses are also given and the experience in inferences obtained with CrossLexica CDB is briefly discussed.
AB - Texts in natural languages consist of words that are syntactically linked and semantically combinable-like political party, pay attention, or brick wall. Such semantically plausible combinations of two content words, which we hereafter refer to as collocations, are important knowledge in many areas of computational linguistics. We consider a lexical resource that provides such knowledge-a collocation database (CBD). Since such databases cannot be complete under any reasonable compilation procedure, we consider heuristic-based inference mechanisms that predict new plausible collocations based on the ones present in the CDB, with the help of a WordNet-like thesaurus. If an available collocation combines the entries A and B, and B is 'similar' to C, then A and C supposedly constitute a collocation of the same category. Also, we touch upon semantically induced morphological categories suiting for such inferences. Several heuristics for filtering out wrong hypotheses are also given and the experience in inferences obtained with CrossLexica CDB is briefly discussed.
KW - Collocations
KW - Enrichment
KW - Hyperonyms
KW - Inference rules
KW - Meronyms
KW - Synonyms
UR - http://www.scopus.com/inward/record.url?scp=0035722195&partnerID=8YFLogxK
M3 - Artículo de la conferencia
AN - SCOPUS:0035722195
SN - 0884-3627
VL - 3
SP - 1688
EP - 1692
JO - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
JF - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
T2 - 2001 IEEE International Conference on Systems, Man and Cybernetics
Y2 - 7 October 2001 through 10 October 2001
ER -