Semantic associations and confluences in paradigmatic networks

Gaume, Bruno; Duvignau, Karine; Vanhove, Martine

doi:10.1075/slcs.106.11gau

Cited by 9 publications

(9 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One can repeat this operation until the expected number of edges is obtained. 11 Secondly we used the PROX approach proposed by (Gaume et al, 2009). It is a stochastic method designed for studying "Hierarchical Small Worlds".…”

Section: Improving Synonymy In Wiktionary Bymentioning

confidence: 99%

See 1 more Smart Citation

Wiktionary and NLP

Navarro

Sajous

Gaume

et al. 2009

Proceedings of the 2009 Workshop on the People's Web Meets NLP Collaboratively Constructed Semantic Resources - People's Web '0

Self Cite

View full text Add to dashboard Cite

Wiktionary, a satellite of the Wikipedia initiative, can be seen as a potential resource for Natural Language Processing. It requires however to be processed before being used efficiently as an NLP resource. After describing the relevant aspects of Wiktionary for our purposes, we focus on its structural properties. Then, we describe how we extracted synonymy networks from this resource. We provide an in-depth study of these synonymy networks and compare them to those extracted from traditional resources. Finally, we describe two methods for semiautomatically improving this network by adding missing relations: (i) using a kind of semantic proximity measure; (ii) using translation relations of Wiktionary itself. Note: The experiments of this paper are based on Wiktionary's dumps downloaded in year 2008. Differences may be observed with the current versions available online.

show abstract

Section: Improving Synonymy In Wiktionary Bymentioning

confidence: 99%

“…For example, Prox adds relations such as hypernyms (to uncover/to peel) or inter-domain 'synonyms' (to skin/to peel). This is due to high clustering (see §3.1) and to the fact that clusters in synonymy networks correlates with language concepts Gaume et al, 2009;Fellbaum, 1999).…”

Section: Improving Synonymy In Wiktionary Bymentioning

confidence: 99%

Wiktionary and NLP

Navarro

Sajous

Gaume

et al. 2009

Proceedings of the 2009 Workshop on the People's Web Meets NLP Collaboratively Constructed Semantic Resources - People's Web '0

Self Cite

View full text Add to dashboard Cite

show abstract

“…As mentioned above, the structure of the lexical network we are building relies on the notions of nodes and relations between nodes, as it was initially introduced in the end of 1960s by Collins and Quillian (1969), developed in Sowa and Zachman (1992), used in the small worlds by Gaume et al (2007), and more recently clarified by Polguère (2014). Every node of the network is composed of a label (which is a term or an expression, or potentially any kind of string) grouping together all of its possible meanings.…”

Section: Inside the Jdm Lexical Networkmentioning

confidence: 99%

Type Theories and Lexical Networks: using Serious Games as the basis for Multi-Sorted Typed Systems

Chatzikyriakidis

Lafourcade²,

Ramadier

et al. 2017

JLM

View full text Add to dashboard Cite

In this paper, we show how a rich lexico-semantic network which has been built using serious games, JeuxDeMots, can help us in grounding our semantic ontologies in doing formal semantics using rich or modern type theories (type theories within the tradition of Martin Löf). We discuss the issue of base types, adjectival and verbal types, hyperonymy/hyponymy relations as well as more advanced issues like homophony and polysemy. We show how one can take advantage of this wealth of lexical semantics in a formal compositional semantics framework. We argue that this is a way to sidestep the problem of deciding what the type ontology should look like once a move to a many sorted type system has been made. Furthermore, we show how this kind of information can be extracted from a lexico-semantic network like JeuxDeMots and inserted into a proof-assistant like Coq in order to perform reasoning tasks.

show abstract

“…The structure of the lexical network we are building is composed of nodes and links between nodes, as it was initially introduced in the end of 1960s by [1], developed in [2], used in the small worlds by [3] and [4], and more recently clarified by [5]. A node of the network refers to a term (or a multiple word expression), usually in its canonical form (lemma).…”

Section: Structure Of the Lexical Networkmentioning

confidence: 99%

“…A game takes place between two players, in an asynchronous way, based on the concordance of their propositions. When a first player begins a game, an instruction concerning a type of competence (synonyms, opposite, domains …) is displayed, as well as a term 4 T randomly picked in a base of terms. This player has then a limited time to answer by giving propositions which, to his mind, correspond to the instruction applied to the term T. The same term, along the same instruction, is afterwards proposed to another player; the process is then identical.…”

Section: Principle Of the Softwarementioning

confidence: 99%

Computing Trees of Named Word Usages from a Crowdsourced Lexical Network

Lafourcade

Joubert

2010

10.14746/il

View full text Add to dashboard Cite

Abstract. Thanks to the participation of a large number of persons via webbased games, a large-sized evolutionary lexical network is available for French. With this resource, we tackled the question of the determination of the word usages of a term, and then we introduced the notion of similarity between these various word usages. So, for a given term, we were able to build its word usage tree: the root groups together all its possible usages and a search in the tree corresponds to a refinement of these word usages. The labelling of the various nodes of the word usage tree of a term is made during a breadth-first search: the root is labelled by the term itself and each node of the tree is labelled by a term stemming from the clique or quasi-clique this node represents. We show on a precise example that it is possible that some nodes of the tree, often leaves, cannot be labelled without ambiguity. This paper ends with an evaluation about word usages detected in our lexical network.

show abstract

Semantic associations and confluences in paradigmatic networks

Cited by 9 publications

References 31 publications

Wiktionary and NLP

Wiktionary and NLP

Type Theories and Lexical Networks: using Serious Games as the basis for Multi-Sorted Typed Systems

Computing Trees of Named Word Usages from a Crowdsourced Lexical Network

Contact Info

Product

Resources

About