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"Fellbaum, Christiane"
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Large, huge or gigantic? Identifying and encoding intensity relations among adjectives in WordNet
We propose a new semantic relation for gradable adjectives in WordNet, which enriches the present, vague, similar relation with information on the degree or intensity with which different adjectives express a shared attribute. Using lexical-semantic patterns, we mine the Web for evidence of the relative strength of adjectives like \"large\", \"huge\" and \"gigantic\" with respect to their attribute (\"size\"). The pairwise orderings we derive allow us to construct scales on which the adjectives are located. To represent the intensity relation among gradable adjectives in WordNet, we combine ordered scales with the current WordNet dumbbells based on the relation between a pair of central adjectives and a group of undifferentiated semantically similar adjectives. A new intensity relation links the adjectives in the dumbbells and their concurrent representation on scales. Besides capturing the semantics of gradable adjectives in a way that is both intuitively clear as well as consistent with corpus data, the introduction of an intensity relation would potentially result in several specific benefits for NLP.
Journal Article
Erratum to: Large, huge or gigantic? Identifying and encoding intensity relations among adjectives in WordNet
Issue Title: Special Issues: \"Computational Semantic Analysis of Language: SemEval-2010\" and \"Wordnets and Relations\"
Journal Article
Challenges for a multilingual wordnet
Wordnets have been created in many languages, revealing both their lexical commonalities and diversity. The next challenge is to make multilingual wordnets fully interoperable. The EuroWordNet experience revealed the shortcomings of an interlingua based on a natural language. Instead, we propose a model based on the division of the lexicon and a language-independent, formal ontology that serves as the hub interlinking the language-specific lexicons. The ontology avoids the idiosyncracies of the lexicon and furthermore allows formal reasoning about the concepts it contains. We address the division of labor between ontology and lexicon. Finally, we illustrate our model in the context of a domain-specific multilingual information system based on a central ontology and interconnected wordnets in seven languages.
Journal Article
Making fine-grained and coarse-grained sense distinctions, both manually and automatically
In this paper we discuss a persistent problem arising from polysemy: namely the difficulty of finding consistent criteria for making fine-grained sense distinctions, either manually or automatically. We investigate sources of human annotator disagreements stemming from the tagging for the English Verb Lexical Sample Task in the SENSEVAL-2 exercise in automatic Word Sense Disambiguation. We also examine errors made by a high-performing maximum entropy Word Sense Disambiguation system we developed. Both sets of errors are at least partially reconciled by a more coarse-grained view of the senses, and we present the groupings we use for quantitative coarse-grained evaluation as well as the process by which they were created. We compare the system's performance with our human annotator performance in light of both fine-grained and coarse-grained sense distinctions and show that well-defined sense groups can be of value in improving word sense disambiguation by both humans and machines. [PUBLICATION ABSTRACT]
Journal Article
Formal Ontology in Information Systems
Researchers in areas such as artificial intelligence, formal and computational linguistics, biomedical informatics, conceptual modeling, knowledge engineering and information retrieval have come to realise that a solid foundation for their research calls for serious work in ontology, understood as a general theory of the types of entities and relations that make up their respective domains of inquiry. In all these areas, attention is now being focused on the content of information rather than on just the formats and languages used to represent information. The clearest example of this development is provided by the many initiatives growing up around the project of the Semantic Web. And, as the need for integrating research in these different fields arises, so does the realisation that strong principles for building well-founded ontologies might provide significant advantages over ad hoc, case-based solutions. The tools of formal ontology address precisely these needs, but a real effort is required in order to apply such philosophical tools to the domain of information systems. Reciprocally, research in the information sciences raises specific ontological questions which call for further philosophical investigations. The purpose of FOIS is to provide a forum for genuine interdisciplinary exchange in the spirit of a unified effort towards solving the problems of ontology, with an eye to both theoretical issues and concrete applications. This book contains a wide range of areas, all of which are important to the development of formal ontologies.
eBook
Semantic Labeling of Nonspeech Audio Clips
Human communication about entities and events is primarily linguistic in nature. While visual representations of information are shown to be highly effective as well, relatively little is known about the communicative power of auditory nonlinguistic representations. We created a collection of short nonlinguistic auditory clips encoding familiar human activities, objects, animals, natural phenomena, machinery, and social scenes. We presented these sounds to a broad spectrum of anonymous human workers using Amazon Mechanical Turk and collected verbal sound labels. We analyzed the human labels in terms of their lexical and semantic properties to ascertain that the audio clips do evoke the information suggested by their pre-defined captions. We then measured the agreement with the semantically compatible labels for each sound clip. Finally, we examined which kinds of entities and events, when captured by nonlinguistic acoustic clips, appear to be well-suited to elicit information for communication, and which ones are less discriminable. Our work is set against the broader goal of creating resources that facilitate communication for people with some types of language loss. Furthermore, our data should prove useful for future research in machine analysis/synthesis of audio, such as computational auditory scene analysis, and annotating/querying large collections of sound effects.
Journal Article
WordNet Then and Now
We briefly discuss the origin and development of WordNet, a large lexical database for English. We outline its design and contents as well as its usefulness for Natural Language Processing. Finally, we discuss crosslinguistic WordNets and complementary lexical resources.
Journal Article
Introduction to the special issue: On wordnets and relations
Issue Title: Special Issues: \"Computational Semantic Analysis of Language: SemEval-2010\" and \"Wordnets and Relations\"
Journal Article