Entanglement and Semantics : Application to Language Processing

Abstract : A lexeme can be represented as a vector in a Hilbert space. Each element of the vector represents the weight of a semantic relation with a second vector: the context of a second lexeme. Two query operators are defined in a way that they attribute the value +1 to the component of the state that corresponds to the word meaning we are interested in, and -1 in the orthogonal direction. Entangled states have been used to detect semantic relationships in Information Retrieval (IR). In particular, since the first operator corresponds to negation and the conditional gate corresponds to an implication in classical logic, they can represent two basic semantic relationships : hyponymy (e.g. genus-species) and antonymy (e.g. masculine-feminine). In fact, according to Semantics, if A and B are antonymic terms, then A is an hyponym of (i.e. implies) not-B as in the Gremias semiotic square. We underline how the relations of a given semantic universe, and the corresponding result of our operators, depends only on the considered text. Among others, this analogy suggests the application of quantum-based models to language and IR.
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Francesco Galofaro, Zeno Toffano, Bich-Liên Doan, Adam Shimi. Entanglement and Semantics : Application to Language Processing. Colloque IQFA 2015, Nov 2015, Palaiseau, France. 2015, 〈http://iqfacolloq2015.sciencesconf.org/〉. 〈hal-01261840〉

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