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Antonymy and Conceptual Vectors

Antonymy and Conceptual Vectors. Didier Schwab, Mathieu Lafourcade, Violaine Prince. presented by Ch. Boitet (works with M. Lafourcade on conceptual vectors & UNL). Laboratoire d’informatique, de robotique Et de microélectronique de Montpellier CNRS - Université Montpellier II. Outline.

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Antonymy and Conceptual Vectors

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  1. Antonymy and Conceptual Vectors Didier Schwab, Mathieu Lafourcade, Violaine Prince presented by Ch. Boitet (works with M. Lafourcade on conceptual vectors & UNL) Laboratoire d’informatique, de robotique Et de microélectronique de Montpellier CNRS - Université Montpellier II

  2. Outline • The main idea • Background on conceptual vectors • How we use CVs • & why we need to distinguish CVs of antonyms • Brief study of antonymies • Representation of antonymies • Measure for « antonymousness » Antonymy and Conceptual Vectors

  3. The main idea • Work on meaning representation in NLP, using conceptual vectors (CV) • applications = WSD & thematic indexing • but V(existence) = V(non-existence) ! • basic « concepts » activated the same • Idea: • use lexical functions to improve the adequacy • For this, « transport » the lexical functions in the vector space Antonymy and Conceptual Vectors

  4. Background on conceptual vectors • Lexical Item = ideas = combination of concepts = Vector V • Ideas space = vector space (generator space) • Concept = idea = vector Vc • Vc taken from a thesaurus hierarchy (Larousse) • translation of Roget’s thesaurus, 873 leaf nodes • the word ‘peace’ has non zero values for concept PEACE and other concepts Antonymy and Conceptual Vectors

  5. Our conceptual vectors Thesaurus • H : thesaurus hierarchy — K concepts Thesaurus Larousse = 873 concepts • V(Ci) : <a1, …, ai, … , a873> aj = 1/ (2 ** Dum(H, i, j)) 1/16 1/16 1/4 1 1/4 1/4 1/64 1/64 4 2 6 Antonymy and Conceptual Vectors

  6. Conceptual vectors Conceptc4: ‘PEACE’ peace conflict relations hierarchical relations society The world, manhood Antonymy and Conceptual Vectors

  7. Conceptual vectors Term “peace” c4:’PEACE’ Antonymy and Conceptual Vectors

  8. exchange profit finance Antonymy and Conceptual Vectors

  9. Angular or « thematic » distance • Da(x,y) = angle(x,y) = acos(sim(x,y)) = acos(x.y /|x ||y |) • 0 ≤ D(x,y) ≤  (positive components) • If 0 then x and y are colinear : same idea. • If /2 : nothing in common. x y Antonymy and Conceptual Vectors

  10. Thematic Distance (examples) • Da(anteater , anteater ) = 0 (0°) • Da(anteater , animal ) = 0,45 (26°) • Da(anteater , train ) = 1,18 (68°) • Da(anteater , mammal ) = 0,36 (21°) • Da(anteater , quadruped ) = 0,42 (24°) • Da(anteater , ant ) = 0,26 (15°) thematic distance ≠ ontological distance Antonymy and Conceptual Vectors

  11. Vector Proximity • Function V gives the vectors closest to a lexical item. V (life) = life, alive, birth… V (death) = death, to die, to kill… Antonymy and Conceptual Vectors

  12. How we build & use conceptual vectors • Conceptual vectors give thematic representations • of word senses • of words (averaging CVs of word senses) • of the content (« ideas ») of any textual segment • New CVs for word senses are permanently learned from NL definitions • coming from electronic dictionaries • CVs of word senses are permanently recomputed • for French, 3 years, 100000 words, 300000 CVs Antonymy and Conceptual Vectors

  13. Definitions Conceptual vectors base Human usage dictionaries SYGMART Morphosyntactic analysis New Vector Continuous building of the conceptual vectors database Antonymy and Conceptual Vectors

  14. We should distinguish CVs of different but related words… Non-existent : who or which does not exist cold : #ant# warm, hot • Without a specific treatment, we get • V(non-existence) = V(existence) • V(cold) = V(hot) • We want to obtain • V(non-existence) ≠ V(existence) • V(cold) ≠ V(hot) Antonymy and Conceptual Vectors

  15. …in order to improve applications and resources • Applications: more precision • Thematic analysis of texts • Thematic analysis of definitions • Resources: coherence & adequacy • General coherence of the CV data base • Conceptual Vector quality (adequacy) Antonymy and Conceptual Vectors

  16. Lexical functions may help! • Lexical function (Mel’tchuk): • WS  {WS1…WSn} • synonymy (#Syn#), antonymy (#Anti#), intensification (#Magn#)… • Examples : • #Syn# (car) = {automobile} • #Anti# (respect) = {disrespect; disdain} • #Sing# (fleet) = {boat, ship; embarcation} Antonymy and Conceptual Vectors

  17. Method: transport the LFs as functions on the CV space • e.g. for antonymy, • to get V(non-existence) ≠ V(existence) • find vector function Anti such that: • V(non-existence) • = V(#Anti#(existence)) = Anti (V(existence)) • similarly for other lexical functions • we simply began by studying antinomy Antonymy and Conceptual Vectors

  18. Brief study of antonymy Definition : Two lexical items are in antonymy relation if there is a symmetry between their semantic components relatively to an axis • Antonymy relations depend on the type of medium that supports symmetry • There are several types of antonymy • On the axis, there are fixed points: • Anti (V(car)) = V(car) because #Anti# (car) =  Antonymy and Conceptual Vectors

  19. 1- Complementary antonymy Values are boolean & symmetric (01) Examples : event/non-event dead/alive existence/non-existence He is present  He is not absent He is absent  He is not present Antonymy and Conceptual Vectors

  20. 2- Scalar antonymy • Values are scalar • Symmetry is relative to a reference value Examples : cold/hot, small/tall This man is small  This man is not tall This man is tall  This man is not small This man is neither tall nor small reference value = « of medium height » Antonymy and Conceptual Vectors

  21. 3- Dual Antonymy (1) • Conversive duals same semantics but inversion of roles Examples : sell/buy, husband/wife, father/son Jack is John’s son John is Jack’s father Jack sells a car to John  John buys a car from Jack Antonymy and Conceptual Vectors

  22. 3- Dual Antonymy (2) • Contrastive duals contrastive expressions accepted by usage • Cultural : sun/moon, yin/yang • Associative : question/answer • Spatio-temporal : birth/death, start/finish Antonymy and Conceptual Vectors

  23. Coherence and adequacy of the base • Learning bootstrap based on a kernel composed of pre-computed vectors considered as adequate • Learning must be coherent = preserve adequacy • Adequacy = judgement that activations of concepts (coordinates) make sense for the meaning corresponding to a definition • For coherence improvement, we use semantic relations between terms Antonymy and Conceptual Vectors

  24. Antonymy function • Based on the antonym vectors of concepts : one list for each kind of antonymy Antic (EXISTENCE) = V (NON-EXISTENCE) Antis (HOT) = V (COLD) Antic (GAME) = V (GAME) • Anti (X,C) builds the vector « opposite » of vector X in context C Antonymy and Conceptual Vectors

  25. Construction of the antonym vector of X in context C • The method is to focus on the salient notions in V(X) and V(C) • If the notions can be opposed, then the antonym should have the inverse ideas in the same proportions • The following formula was obtained after several experiments Antonymy and Conceptual Vectors

  26. Construction of the antonym vector (2) N • AntiR (V(X), V(C)) =  Pi *AntiC (Ci, V(C)) • Pi= V * max (V(X), V(Ci)) • Not symmetrical • Stress more on vector X than on context C • Consider an important idea of the vector to oppose even if it is not in the referent i=1 1+CV(V(X)) Xi Antonymy and Conceptual Vectors

  27. Results • V (#Anti# (death, life & death)) = (LIFE 0,3), (birth 0,48), (alive 0,54)… • V (#Anti# (life, life & death)) = (death 0,336), (killer 0,45), (murdered 0,53)… • V (#Anti# (LIFE)) = (DEATH0,034), (death 0,43), (killer 0,53)... Antonymy and Conceptual Vectors

  28. Antonymy evaluation measure • Assess « how much » two lexical items are antonymous • Manti(A,B) = DA(AB, Anti(A,C) Anti(B,C)) A Anti(B) Anti(A) B Antonymy and Conceptual Vectors

  29. Examples • Manti (EXISTENCE, NON-EXISTENCE) = 0,03 • Manti (existence, non-existence) = 0,44 • Manti (EXISTENCE, CAR) = 1,45 • Manti (existence, car) = 1,06 • Manti (CAR, CAR) = 0,006 • Manti (car, car) = 0,407 Antonymy and Conceptual Vectors

  30. Conclusion and perspectives • Progress so far : • Antonymy definition based on a notion of symmetry • Implemented formula to compute an antonym vector • Implemented measure to assess the level of antonymy between two items • Perspectives : • Use of the symbolic opposition found in dictionaries • Search the opposite meaning of a word • Study of the other semantic relations • (hyperonymy/hyponymy, meronymy/holonymy…) Antonymy and Conceptual Vectors

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