Is it possible to use sense inventories to improve Web search results diversity for one word queries? To answer this question, we focus on two broad-coverage lexical resources of a different nature: WordNet, as a de-facto standard used in Word Sense Disambiguation experiments; and Wikipedia, as a large coverage, updated encyclopaedic resource which may have a better coverage of relevant senses ...

Relations annotation and inference in a lexical-semantic network : application to radiology Domain specific ontologies are invaluable despite many challenges associated with their development. In most cases, domain knowledge bases are built with very limited scope without considering the benefits of plunging domain knowledge to a general ontology. Furthermore, most existing resources lack meta-...

GLAWI is a free, large-scale and versatile Machine-Readable Dictionary (MRD) that has been extracted from the French language edition of Wiktionary, called Wiktionnaire. In (Sajous and Hathout, 2015), we introduced GLAWI, gave the rationale behind the creation of this lexicographic resource and described the extraction process, focusing on the conversion and standardization of the heterogeneous...

In this paper we describe our ongoing work concerning lexical modeling in the LIMSI broadcast transcription system for German. Lexical decomposition is investigated with a twofold goal: lexical coverage optimization and improved letter-to-sound conversion. A set of about 450 decompounding rules, developed using statistics from a 300M word corpus, reduces the OOV rate from 4.5% to 4.0% on a 30k ...

We present a lexical resource comprising morphological and syntactic information. The resource is realised as a relational database, which facilitates the access and administration of the data. Sophisticated tools have been developed to allow a user-friendly usage of the resource. One application, a broad coverage parser, which makes use of both the morphological and syntactic part of the datab...

Coverage has been a constant thorn in the side of deployed deep linguistic processing applications, largely because of the difficulty in constructing, maintaining and domaintuning the complex lexicons that they rely on. This paper reviews various strands of research on deep lexical acquisition (DLA), i.e. the (semi-)automatic creation of linguistically-rich language resources, particularly from...

We examine the feasibility of harvesting a wide-coverage lexicon of English verbs from the FrameNet semantically annotated corpus, intended for use in a practical natural language understanding (NLU) system. We identify a range of constructions for which current annotation practice leads to problems in deriving appropriate lexical entries, for example imperatives, passives and control, and disc...

This paper describes a new automatic approach for extracting conceptual distinctions from dictionary definitions. A broad-coverage dependency parser is first used to extract the lexical relations from the definitions. Then the relations are disambiguated using associations learned from tagged corpora. This contrasts with earlier approaches using manually developed rules for disambiguation.

Based on an architecture that allows to combine statistical machine translation (SMT) with rule-based machine translation (RBMT) in a multi-engine setup, we present new results that show that this type of system combination can actually increase the lexical coverage of the resulting hybrid system, at least as far as this can be measured via BLEU score.

Coverage has been a constant thorn in the side of deployed deep linguistic processing applications, largely because of the difficulty in constructing, maintaining and domain-tuning the complex lexicons that they rely on. This paper reviews various strands of research on deep lexical acquisition (DLA), i.e. the (semi-)automatic creation of linguistically-rich language resources, particularly fro...