We present the first visualization of document content which takes advantage of the human-created structure in lexical databases. We use the WordNet hyponymy (IS-A) relationship as the structure for radial, space-filling trees which quickly reveal the concepts contained within a document of interest. Interactive techniques of zoom, filter, and details-on-demand support document analysis. The vi...

In this paper, we describe how ontologies can be built automatically from definitions obtained by searching Wikipedia for lexico-syntactic patterns based on the hyponymy relation. First, we describe how definitions are retrieved and processed while taking into account both recall and precision. Further, concentrating only on precision, we show how a consistent and useful domain ontology can be ...

The goal of this paper is to provide computable account for some definite descriptions. To this end, we define in terms of inclusion the notion of distinguishing description and of distinguishable entities introduced by [Dale 89]. These def'mitions allow us to give conditions of wellformedness for incomplete distinguishing descriptions. We also extend the notion of distinguishing description to...

We present the first visualization of document content which takes advantage of the human-created structure in lexical databases. We use an accepted design paradigm to generate visualizations which improve the usability and utility of WordNet as the backbone for document content visualization. A radial, space-filling layout of hyponymy (IS-A relation) is presented with interactive techniques of...

Instances (“Mozart”) are ontologically distinct from concepts or classes (“composer”). Natural language encompasses both, but instances have received comparatively little attention in distributional semantics. Our results show that instances and concepts differ in their distributional properties. We also establish that instantiation detection (“Mozart – composer”) is generally easier than hyper...

In this paper, we evaluate different lexico-syntactic patterns in regard to their usefulness for ontology building. Each pattern is analysed individually to determine its respective probability to return the hyponymy relation. We also create different ontologies according to this accuracy criteria to show how it influences the resulting ontology. Using patterns with a success rate over 80% lead...

This paper describes work in progress to use clustering to create a lexicon of words that engage in the lexico-semantic relationship known as grading. While other resources like thesauri and taxonomies exist detailing relationships such as synonymy, antonymy, and hyponymy, we do not know of any thorough resource for grading. This work focuses on identifying the words that may participate in thi...

Preliminary results from an experimental study of readers’ perceptions of lexical cohesion and lexical semantic relations in text are presented. Readers agree on a common “core” of groups of related words and exhibit individual differences. The majority of relations reported are “non-classical” (not hyponymy, meronymy, synonymy, or antonymy). A group of commonly used relations is presented. The...

This paper proposes a novel framework called bilingual co-training for a largescale, accurate acquisition method for monolingual semantic knowledge. In this framework, we combine the independent processes of monolingual semanticknowledge acquisition for two languages using bilingual resources to boost performance. We apply this framework to largescale hyponymy-relation acquisition from Wikipedi...