Is class inclusion (hyponymy) a more primitive or simpler semantic relation than synonymy? This question was addressed by comparing the time required to identify examples of the two relations in a semantic decision task. In two experiments subjects made true~false decisions about statements of the form "An A is a B. "" In Experiment 1 category-member and synonym pairs were randomly intermixed; ...

Relationship acquisition has always contributed as an important enhancement to Natural Language Processing. Using “definition extraction” methods proved to be a very useful approach, not only for relationship extraction but also for enhancing the limited coverage of words in WordNet. It also played a major role in developing question answer systems and ontology learning for unrestricted data. V...

In this study, we apply pattern-based methods to text for extracting lexical data, in particular the hypernymy relation. We automatically derive thousands of interesting lexical patterns like such NP as NP and evaluate the performance of these patterns by comparing the information they extract from a newspaper corpus with the information in the Dutch part of EuroWordNet. Additionally we investi...

On a pilot corpus of Dutch medical encyclopedia texts, we focus on the mechanism of taxonomic inference that involves the extraction of co-hyponym terms, and the taxonomic or domain-specific lexicosemantic relation in the form of a textual hypothesis, which coordinates these. An initial set of inference elements can be acquired by syntactic and semantic alignment, additionally driven by documen...

We describe how hierarchical ontologies are used for classifying products, as well as for answering queries. For classifying and scoring product descriptions and queries in an electronic-commerce search engine, we make use of declarative hypernym/hyponym and meronym/holonym hierarchies, such as the sense hierarchies provided by WordNet. Retrieval is also aided by use of the ontology. Results of...

The acquisition of explicit semantics is still a research challenge. Approaches for the extraction of semantics focus mostly on learning hierarchical hypernym-hyponym relations. The extraction of co-hyponym and co-meronym sibling semantics is performed to a much lesser extent, though they are not less important in ontology engineering. In this paper we will describe and evaluate the XTREEM-SG (...

We compare two processing methods for a single natural language processing task. One uses a treebank created with a full parser while the other restricts itself to lexical and part-of-speech information. We show that for the task under investigation, automatic extraction of hypernym-hyponym pairs from text, the former does not outperform the latter. We compare the output of the two approaches a...

We report on the result of investigating which relationship is important among hypernym and hyponym relationships in retrieval keyword expansion. Moreover, we report the effect of the keyword expansion and the contents complement for spoken document retrieval for SCR lecture retrieval task and SCR passage retrieval task. Spoken Document Retrieval by contents complement and keyword expansion usi...