OntoLearn is a system for automatic acquisition of specialized ontologies from domain corpora, based on a syntactic pattern matching technique for word sense disambiguation, called structural semantic interconnection (SSI). We use SSI to extract from corpora complex domain concepts and create a specialized version of WordNet. In order to facilitate the task of domain specialists who inspects an...

We review in detail here a polished version of the systems with which we participated in the Senseval2 competition English tasks (all words and lexical sample). It is based on a combination of selectional preference measured over a large corpus and hierarchical information taken from WordNet, as well as some additional heuristics. We use that information to expand sense glosses of the senses in...

Abstract Following a large body of research on metadiscourse in academic writing, this paper explores one feature textual metadiscourse, code glosses, English L2 texts written by Czech university students. The study draws Hyland’s model (2005), which characterizes glosses as devices that elaborate propositional meanings rephrasing or explaining what has been said. Thus, they can help readers un...

A considerable amount of research has already established that academic writing is an interactive accomplishment, the success which largely depends on appropriate writer-reader relationship. Yet, nature this relationship been subject few studies. Also scarce are studies how writers address needs their readers and so, through elaboration, manage interactions with them. Drawing a corpus 68 articl...

We describe an annotation experiment combining topics from lexicography and Word Sense Disambiguation. It involves a lexicon (Pattern Dictionary of English Verbs, PDEV), an existing data set (VPS-GradeUp), and an unpublished data set (RTE in PDEV Implicatures). The aim of the experiment was twofold: a pilot annotation of Recognizing Textual Entailment (RTE) on PDEV implicatures (lexicon glosses...

This paper presents a method of unsupervised word sense discrimination that augments co–occurrence feature vectors derived from raw untagged corpora with information from the glosses found in a machine readable dictionary. Each content word that occurs in the context of a target word to be discriminated is represented by a co-occurrence feature vector. Each of these vectors is augmented with th...

In the present study, introductory-level German students read a simplified story and learned the meanings of new German words by reading English translations in marginal glosses versus trying to infer (i.e., guess) their translations. Students who inferred translations were given feedback in English or in German, or no feedback at all. Although immediate retention of new vocabulary was better f...