Mapping between Dependency Structures and Compositional Semantic Representations

7991

Authors

nan

Abstract

AbstractThis paper investigates the mapping between two semantic formalisms, namely the tectogrammatical layer of the Prague Dependency Treebank 2.0 (PDT) and (Robust) Minimal Recursion Semantics ((R)MRS). It is a first attempt to relate the dependency-based annotation scheme of PDT to a compositional semantics approach like (R)MRS. A mapping algorithm that converts PDT trees to (R)MRS structures is developed, associating (R)MRSs to each node on the dependency tree. Furthermore, composition rules are formulated and the relation between dependency in PDT and semantic heads in (R)MRS is analyzed. It turns out that structure and dependencies, morphological categories and some coreferences can be preserved in the target structures. Moreover, valency and free modifications are distinguished using the valency dictionary of PDT as an additional resource. The validation results show that systematically correct underspecified target representations can be obtained by a rule-based mapping approach, which is an indicator that (R)MRS is indeed robust in relation to the formal representation of Czech data. This finding is novel, for Czech, with its free word order and rich morphology, is typologically different than languages analyzed with (R)MRS to date.

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Labeled Text

AbstractThis paper investigates the mapping between two semantic formalisms, namely the tectogrammatical layer of the Prague Dependency Treebank 2.0 (PDT) and (Robust) Minimal Recursion Semantics ((R)MRS). It is a first attempt to relate the dependency-based annotation scheme of PDT to a compositional semantics approach like (R)MRS. A mapping algorithm that converts PDT trees to (R)MRS structures is developed, associating (R)MRSs to each node on the dependency tree. Furthermore, composition rules are formulated and the relation between dependency in PDT and semantic heads in (R)MRS is analyzed. It turns out that structure and dependencies, morphological categories and some coreferences can be preserved in the target structures. Moreover, valency and free modifications are distinguished using the valency dictionary of PDT as an additional resource. The validation results show that systematically correct underspecified target representations can be obtained by a rule-based mapping approach, which is an indicator that (R)MRS is indeed robust in relation to the formal representation of Czech data. This finding is novel, for Czech, with its free word order and rich morphology, is typologically different than languages analyzed with (R)MRS to date.

Publication Details

Paper ID:
7991
Year:
2010
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan