The automatic compilation of bilingual dictionaries from comparable corpora has been successful for single-word terms (SWTs), but remains disappointing for multi-word terms (MWTs). One of the main problems is the insufficient coverage of the bilingual dictionary. Using the compositional translation method improved the results, but still shows some limits for MWTs of different syntactic structur...

This paper uses human verb associations as the basis for an investigation of verb properties, focusing on semantic verb relations and prominent nominal features. First, the lexical semantic taxonymy GermaNet is checked on the types of classic semantic relations in our data; verbverb pairs not covered by GermaNet can help to detect missing links in the taxonomy, and provide a useful basis for de...

Alignment of words and multiword units plays an important role in many natural language processing applications, such as example-based machine translation, transfer rule learning for machine translation, bilingual lexicography, word sense disambiguation, etc. In this paper we describe LIHLA, a lexical aligner which uses bilingual probabilistic lexicons generated by a freely available set of too...

A graph-based distance between Wikipedia articles is defined using a random walk model, which estimates visiting probability (VP) between articles using two types of links: hyperlinks and lexical similarity relations. The VP to and from a set of articles is then computed, and approximations are proposed to make tractable the computation of semantic relatedness between every two texts in a large...

Lexical knowledge bases (LKBs), such as WordNet, have been shown to be useful for a range of language processing tasks. Extending these resources is an expensive and time-consuming process. This paper describes an approach to address this problem by automatically generating a mapping from WordNet synsets to Wikipedia articles. A sample of synsets has been manually annotated with article matches...

Lexical cohesion is an important device for signalling text organisation. In this paper, we investigate to what extent idiomatic expressions participate in the cohesive structure of a text. We look at the problem both from an empirical and a computational perspective. Our results show that both literal and nonliteral expressions exhibit cohesion with their context, though the latter tend to do ...

To segment texts in thematic units, we present here how a basic principle relying on word distribution can be applied on different kind of texts. We start from an existing method well adapted for scientific texts, and we propose its adaptation to other kinds of texts by using semantic links between words. These relations are found in a lexical network, automatically built from a large corpus. W...

When learners acquire new words in a second language (L2), their lexical representations and links are initially imprecise. As new, similar learned, these must become more specific to avoid errors. This study investigated whether contrasting triggers this sharpening process facilitates learning. In multiple-choice learning task, 114 adults acquired orthographically semantically L2 (pseudo)words...

The paper presents and evaluates a parsing system for the automatic annotation of Porguguese text with semantic role tags. All in all, 38 different categories, like agent, patient, location etc. are distinguished. The annotater uses a grammar of 500 hand-written Constraint Grammar rules and exploits syntactic dependency links as well as semantic prototype classes and syntactic function. The int...

We introduce a technique for identifying the most salient participants in a discussion. Our method, MavenRank is based on lexical centrality: a random walk is performed on a graph in which each node is a participant in the discussion and an edge links two participants who use similar rhetoric. We have used MavenRank to identify the most influential members of the US Senate using data from the U...