Distinguishing lexical relations has been a long term pursuit in natural language processing (NLP) domain. Recently, in order to detect lexical relations like hypernymy, meronymy, co-hyponymy etc., distributional semantic models are being used extensively in some form or the other. Even though a lot of efforts have been made for detecting hypernymy relation, the problem of co-hyponymy detection...

This paper describes an automatic method for acquiring hyponymy relations from HTML documents on the WWW. Hyponymy relations can play a crucial role in various natural language processing systems. Most existing acquisition methods for hyponymy relations rely on particular linguistic patterns, such as “NP such as NP”. Our method, however, does not use such linguistic patterns, and we expect that...

The purpose of this article is to identify grammatical and lexical forms cohesion in the discourse april 2022 issue kompas.com site's online news. This uses a descriptive qualitative method with text analysis type research. Data collection techniques are carried out by recording words, phrases, clauses sentences that have forms. Based on data obtained form cohesion, namely efficiency, substitut...

This paper studies the problem of the automatic acquisition of the hyponymy (is-a) relation in sentences and develops a new method for it. In this paper, we treat the task of identifying hyponymy relation as two separate problems and solve them based on the following three techniques: term type’s commonality, sequential patterns, property nouns and domain verbs.

Semantic relationships between words provide relevant information about the whole idea in texts. Existing embedding representation models characterize each word as a vector of numbers with fixed length. These have been used tasks involving text classification, such recommendation and question–answer systems. However, embedded provided by semantic has neglected. Therefore, this paper proposes an...

Research on hyponymy acquisition is a basic and crucial problem in knowledge acquisition from text. In this paper we present a method of hyponymic relation acquisition and verification based on Chinese lexico-syntactic patterns. Firstly, we make use of removable lexicons and sentence patterns that have been semi-automatically obtained to analyze Chinese-isa patterns. Then we use an algorithm th...

Automatic knowledge extraction from such a very large document corpus as the Web is one of the hottest research topics in the domain of Artificial Intelligence and Database technologies. This chapter introduces my object-oriented and the existing methods to extract semantic (e.g., hyponymy and meronymy) and sensory (e.g., visual and aural) knowledge from the Web, and compares them by showing se...

This paper presents the complete and consistent ontological annotation of the nominal part of WordNet. The annotation has been carried out using the semantic features defined in the EuroWordNet Top Concept Ontology and made available to the NLP community. Up to now only an initial core set of 1,024 synsets, the so-called Base Concepts, was ontologized in such a way. The work has been achieved b...

Semantic relations between words, such as hyponymy, synonymy and meronymy, have various information access applications (e.g. Web search) and the automatic extraction of such relations from corpora is an important research problem in natural language processing. For the Japanese language, there exist several linguistic resources that contain these relations, such as the Japanese Wordnet, Nihong...