The important part of semantics of complex sentence is captured as relations among semantic roles in subordinate and main clause respectively. However if there can be relations between every pair of semantic roles, the amount of computation to identify the relations that hold in the given sentence is extremely large. In this paper, for semantics of Japanese complex sentence, we introduce new pr...

Frame semantics is a theory of linguistic meanings, and is considered to be a useful framework for shallow semantic analysis of natural language. FrameNet, which is based on frame semantics, is a popular lexical semantic resource. In addition to providing a set of core semantic frames and their frame elements, FrameNet also provides relations between those frames (hence providing a network of f...

Due to the scale and the decentralized nature of the Semantic Web, heterogeneities among concepts used are the rule rather than the exception. To provide a meaningful basis for tasks like reasoning over or discovery of semantic web services, similarity relationships must be defined among them in a semi-automatic way. Similarity computation schemes with single hierarchical concept relations are ...

The capacity to evaluate causal relations is fundamental to human cognition, and yet little is known of its neurocognitive underpinnings. A functional magnetic resonance imaging study was performed to investigate an hypothesized dissociation between the use of semantic knowledge to evaluate specifically causal relations in contrast to general associative relations. Identical pairs of words were...

The linguistic and conceptual shift in Terminology has led to a more discourse-centered approach with a focus on how terms are used in texts (Temmerman and Kerremans, 2003). This shift has affected the construction of terminological knowledge bases, which have an underlying network of semantic relations. Such a network can be derived from corpus analysis and the extraction of terminological uni...

Automatic discovery of semantic relations between resources is a key issue in Web-based intelligent applications such as document understanding and Web services. This paper explores how to automatically discover the latent semantic relations and their properties based on the existing association rules. Through building semantic matrix by the association rules, four semantic relations can be ext...

This paper proposes a principled approach for analysis of semantic relations between constituents in compound nouns based on lexical semantic structure. One of the difficulties of compound noun analysis is that the mechanisms governing the decision system of semantic relations and the representation method of semantic relations associated with lexical and contextual meaning are not obvious. The...

The automatic extraction of semantic relations between words from textual corpora is an extremely challenging task. The increasing need for language resources supporting Natural language processing (NLP) applications has encouraged the development of automated methods for the extraction of semantic relations between words. The use of corpus statistical and similarity distribution methods can he...

We present a framework for representing three linguistic levels and systems for generating this representation. We focus on a logical level, like LFG’s F-structure, but compatible with Penn Treebanks. While less finegrained than typical semantic role labeling approaches, our logical structure has several advantages: (1) it includes all words in all sentences, regardless of part of speech or sem...

Purpose To propose a comprehensive and semi-automatic method for constructing or updating knowledge organization tools such as thesaurus. Methodology We propose a comprehensive methodology for thesaurus construction and maintenance combining shallow NLP with a clustering algorithm and an information visualization interface. The resulting system TermWatch, extracts terms from a text collection, ...