Objective: To assess the coverage of the Human Phenotype Ontology (HPO) phenotypes in standard terminologies. Methods: We map HPO terms to the UMLS and its source terminologies and compare these lexical mappings to HPO cross-references. Results: Coverage of HPO classes in UMLS is 54% and 30% in SNOMED CT. Lexical mappings largely outnumber cross-references. Conclusions: Our approach can support...

Syntax-based vector spaces are used widely in lexical semantics and are more versatile than word-based spaces (Baroni and Lenci, 2010). However, they are also sparse, with resulting reliability and coverage problems. We address this problem by derivational smoothing, which uses knowledge about derivationally related words (oldish→ old) to improve semantic similarity estimates. We develop a set ...

Lemlat is a morphological analyser for Latin, which shows a remarkably wide coverage of the Latin lexicon. However, the performance of the tool is limited by the absence of proper names in its lexical basis. In this paper we present the extension of Lemlat with a large Onomasticon for Latin. First, we describe and motivate the automatic and manual procedures for including the proper names in Le...

In this paper we present an API for programmatic access to BabelNet – a wide-coverage multilingual lexical knowledge base – and multilingual knowledge-rich Word Sense Disambiguation (WSD). Our aim is to provide the research community with easy-to-use tools to perform multilingual lexical semantic analysis and foster further research in this direction.

One characteristic of NooJ is that its corpus processing engine uses large-coverage linguistic lexical and syntactic resources. This allows NooJ users to perform sophisticated queries that include any of the available morphological, lexical or syntactic properties. In comparison with INTEX, NooJ uses a new technology (.NET), a new linguistic engine, and was designed with a new range of applicat...

We describe how unknown lexical entries are processed in a unification-based framework with large-coverage grammars and how from their usage lexical entries are extracted. To keep the time and space usage during parsing within bounds, information from external sources like Part of Speech (PoS) taggers and morphological analysers is taken into account when information is constructed for unknown ...

The importance of describing regular polysemy in a lexicon has often been outlined, especially in the field of natural language processing (for a good overview of this issue, see (Ravin and Leacock, 2000)). Unfortunately, no existing broad-coverage semantic lexicon has been built following this relatively recent advice. And since producing a broad coverage semantic lexicon is a very time-consum...

In this paper we present a quantitative investigation into the impact of text normalization on lexica and language models for speech recognition in French. The text normalization process defines what is considered to be a word by the recognition system. Depending on this definition we can measure different lexical coverages and language model perplexities, both of which are closely related to t...

A pervasive computing environment consists typically of a large heterogeneous collection of networked devices. This paper describes the use of lexical knowledge to improve a pervasive computing environment. In an ongoing research project, we are exploring ways to enable non-technical users to manage and control their home environment that is particularly hostile. We assume that each device belo...

The focus of this article is the integration of two different perspectives on lexical semantics: Discourse Representation Theory's (DRT) inferentially motivated approach and Semantic Emphasis The-ory's (SET) lexical field based view. A new joined representation format is developed which is exemplified by analyses of German verbs. The benefits thereof are on both sides. DI/T gains basic entries ...