Presupposition relations between verbs are not very well covered in existing lexical semantic resources. We propose a weakly supervised algorithm for learning presupposition relations between verbs that distinguishes five semantic relations: presupposition, entailment, temporal inclusion, antonymy and other/no relation. We start with a number of seed verb pairs selected manually for each semant...

This paper describes a workbench system for constructing a dictionary to interpret compound nouns, which integrates the acquisition of semantic information and interpretation of compound nouns. First, we extract semantic information from a machine readable dictionary and corpora using regular expressions. Then, the semantic relation of compound nouns are interpreted based on semantic relations,...

The article is devoted to the study of the evaluative component of the meaning of lexical means used to describe relations between family members in the novel “In Chancery” by J. Galsworthy. The relevance of t &he study can be attributed to the lack of works devoted to this problem. As the results of our study demonstrate, the words of the lexical-semantic group “family” were mainly used to ver...

This paper presents an approach for detecting semantic relations in noun phrases. A learning algorithm, called semantic scattering, is used to automatically label complex nominals, genitives and adjectival noun phrases with the corresponding semantic relation. 1 Problem description This paper is about the automatic labeling of semantic relations in noun phrases (NPs). The semantic relations are...

The explication of the semantics of geospatial concepts is a crucial research priority which affects various aspects of information representation, formalization, integration, and exchange. The aim of the present paper is twofold. Firstly, it proposes a methodology for the semantic definition of geospatial concepts. The proposal is based on an analysis of the semantics of geospatial concepts de...

In this chapter a mathematical formalization of WordNet that relies on WordNet’s hierarchical and relational structure is described. Conceptual hierarchies are formalized in Formal Concept Analysis (Ganter & Wille, 1996), a theory developed at the Technische Hochschule Darmstadt over the last sixteen years (Section 7.2). This theory can be extended to Relational Concept Analysis by adding furth...

This paper presents novel algorithms for learning semantic relations from an existing ontology or concept hierarchy. The authors suggest recommendation of semantic relations for supporting continuous ontology development, i.e., the development of ontologies during their use in social semantic bookmarking, semantic wiki, or other Web 2.0 style semantic applications. This paper assists users in p...

This paper presents a new method for extracting meaningful relations from unstructured natural language sources. The method is based on information made available by shallow semantic parsers. Semantic information was used (1) to enhance a dependency tree kernel; and (2) to build semantic dependency structures used for enhanced relation extraction for several semantic classifiers. In our experim...