This work introduces SYMPAThy, a data representation model in which the combinatorial properties of a lexical item are described by merging surface and deeper linguistic information. The proposed approach is then evaluated by comparing, for a sample list of verbal idioms, a set of SYMPAThy-based fixedness indexes against the relevant speaker-elicited indexes available in the descriptive norms collected by Tabossi et al. (2011).

This work introduces SYMPAThy, a data representation model in which the combinatorial properties of a lexical item are described by merging surface and deeper linguistic information. The proposed approach is then evaluated by comparing, for a sample list of verbal idioms, a set of SYMPAThy-based fixedness indexes against the relevant speaker-elicited indexes available in the descriptive norms collected by Tabossi et al. (2011).

Mapping the Constructicon with SYMPAThy: Italian Word Combinations between fixedness and productivity

CASTAGNOLI, SARA;
2015-01-01

Abstract

This work introduces SYMPAThy, a data representation model in which the combinatorial properties of a lexical item are described by merging surface and deeper linguistic information. The proposed approach is then evaluated by comparing, for a sample list of verbal idioms, a set of SYMPAThy-based fixedness indexes against the relevant speaker-elicited indexes available in the descriptive norms collected by Tabossi et al. (2011).
2015
This work introduces SYMPAThy, a data representation model in which the combinatorial properties of a lexical item are described by merging surface and deeper linguistic information. The proposed approach is then evaluated by comparing, for a sample list of verbal idioms, a set of SYMPAThy-based fixedness indexes against the relevant speaker-elicited indexes available in the descriptive norms collected by Tabossi et al. (2011).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11393/241622
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