Knowledge-poor corpus-based approaches to natural language processing are attractive in that they do not incur the diiculties associated with complex knowledge bases and real-world inferences. However, these kinds of language processing techniques in isolation often do not suuce for a particular task; for this reason we are interested in nding ways to combine various techniques and improve thei...

In recent times, wordnets have become indispensable resources for Natural Language Processing. However, the creation of wordnets is a time consuming and manpower intensive proposition. This fact has led to attempts at quickly fixing a wordnet using text repositories such as the web and certain corpora, and also by translating an existing wordnet into another language. However, the results of su...

Is class inclusion (hyponymy) a more primitive or simpler semantic relation than synonymy? This question was addressed by comparing the time required to identify examples of the two relations in a semantic decision task. In two experiments subjects made true~false decisions about statements of the form "An A is a B. "" In Experiment 1 category-member and synonym pairs were randomly intermixed; ...

We present the results of an agreement task carried out in the framework of the KNOW Project and consisting in manually annotating an agreement sample totaling 50 sentences extracted from the SenSem corpus. Diambiguation was carried out for all nouns, proper nouns and adjectives in the sample, all of which were assigned EuroWordNet (EWN) synsets. As a result of the task, Spanish WN has been sho...

We introduce HyperLex—a data set and evaluation resource that quantifies the extent of the semantic category membership, that is, type-of relation, also known as hyponymy–hypernymy or lexical entailment (LE) relation between 2,616 concept pairs. Cognitive psychology research has established that typicality and category/class membership are computed in human semantic memory as a gradual rather t...

This paper reports on the main phases of a research which aims at enhancing a maritime terminological database by means of a set of terms belonging to meteorology. The structure of the terminological database, according to EuroWordNet/ItalWordNet model is described; the criteria used to build corpora of specialized texts are explained as well as the use of the corpora as source for term selecti...

Traditional methods for deriving property-based representations of concepts from text have focused on either extracting only a subset of possible relation types, such as hyponymy/hypernymy (e.g., car is-a vehicle) or meronymy/metonymy (e.g., car has wheels), or unspecified relations (e.g., car--petrol). We propose a system for the challenging task of automatic, large-scale acquisition of uncons...

Creating a Natural Language Processing (NLP) application often requires to access lexical-semantic Knowledge Bases (KBs). Recently, Collaborative Knowledge Bases (CKBs) such as Wikipedia and Wiktionary1 have been recognized as promising lexicalsemantic KBs for NLP (Zesch et al., 2008b), complementing traditional Linguistic Knowledge Bases (LKBs). As CKBs differ significantly from LKBs concernin...

The increasing availability of numerous corpora has significantly contributed to the understanding of words in terms of their underlying semantic structures and lexical networks (e.g. COBUILD, WordNet etc.). Through data mining and information retrieval, research in this area has vastly expanded our appreciation that what constitutes lexical knowledge goes beyond synonymy, hyponymy, metonymy, m...

In the big data era, the sizes of datasets have increased dramatically in terms of the number of samples, features, and classes. In particular, there exists usually a hierarchical structure among the classes. This kind of task is called hierarchical classification. Various algorithms have been developed to select informative features for flat classification. However, these algorithms ignore the...