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Entanglement and semantics : application to language processing

Francesco Galofaro, Zeno Toffano, Bich-Liên Doan, Adam Shimi

Published Jan 1, 2015• 0 citations
Publisher

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.

DOI
10.13140/rg.2.1.4681.3528

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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.
Purpose The paper aims to provide a semiotic interpretation of the role played by entanglement in quantum-based models aimed to information retrieval and suggests possible improvements. Actual models are capable of retrieving documents relevant to a query composed of a keyword and its acceptation expressed by a given context. The paper also considers some analogies between this technique and quantum-based approaches in other disciplines to discuss the consequence of this quantum turn, as epistemology and philosophy of language are concerned. Design/methodology/approach We use quantum geometry to design a formal model for textual semiotics. In particular, the authors refer to Greimas’s work on semantics and information theory, to Eco’s writings on semantic memory and to Lotman’s work on a cybernetic notion of culture. Findings Quantum approaches imply a particular point of view on meaning. Meaning is not a real, positive quality of a given word. It is a net of relations constructed in the text, whose value is progressively determined during the reading process. Furthermore, reading is not a neutral operation: to read is to determine meaning. If it is said that, from a general semiotic point of view, meaning is stored in quantum semantic memories and is read/written by semantic machines, then the operation of “reading/writing” is analogous to the operation of measuring in quantum theory: in other terms, meaning is a value, and this implies an instance (not necessarily human) according to which values are valuable. Research limitations/implications The authors are not proposing a complete quantum semantics. At the present, quantum information retrieval can detect the presence of semantic relations. The authors suggest a way to characterize them, leaving open the problem on how to formalize the document as a vector in four-state semantic space. Practical implications A quantum turn shows deep semiotic implications on the approach to language, which shows an immanent semantic organization not reducible to syntax and morphology. This organization is probabilistic and indeterministic and explains to what extent text fixes the meaning of its lexical units. Social implications In the authors’ perspective, signification is not the exclusivity of a human subject. Criticizing Turing test, the great semiotic and cybernetic scholar Jurij Lotman wrote that if we identify “intelligent” and “human”, we raise the failings of an actual form of intelligence to the rank of an essential characteristic. On this line, meaning is considered as a feature of social, artificial and biological systems. Originality/value The adoption of quantum formalism seems in line with cybernetic framework, involving a probabilistic, non-cartesian point of view on meaning aimed to critically discuss the human–machine relation. Furthermore, Quantum theory (QT) implies a phenomenological point of view on the conditions of possibility of meaning.
Big Data re-opened the debate between deterministic and probabilistic methods in linguistics. Semantics seems to be a promising field for their application: Greimas observed how semantic layers are stabilized in a document thanks to redundancy, thus transmitting less information. For example, the context stabilizes one of the possible meanings of ambiguous syntactic structures such as “the chicken is ready to eat.” by reducing the probability of the other meanings.Among different probabilistic algorithms, a model based on quantum geometry could better represent natural language semantics. Semantic relationships seem not commutative [3]; they violates Leibniz's law as it happens in quantum logic; many semantic relationships are not represented by morphosyntactic elements, as the vector state is not observable; the stabilisation of a semantic bind could be modelled by entanglement. We will show how the Bell states can be used to encode the basic fundamental semantic relationships represented by Greimas’s semiotic square, thus providing a clue to develop new algorithms designed for information retrieval.
The theory of logical gates in quantum computation has suggested new forms of quantum logic, called quantum computational logics. The basic semantic idea is the following: the meaning of a sentence α is identified with a quantum information quantity, represented by a density operator of a Hilbert space, whose dimension depends on the logical complexity of α. At the same time, the logical connectives of the language are interpreted as operations defined in terms of quantum logical gates. Standard quantum computational models can be described as special cases of Fock space models, where the meaning of any sentence is localized in a precise sector of a Fock space ℱ. From an intuitive point of view, the increasing number of particles described in the different sectors of ℱ can be interpreted as increasing information.
Tests are essential in Information Retrieval and Data Mining in order to evaluate the effectiveness of a query. An automatic measure tool intended to exhibit the meaning of words in context has been developed and linked with Quantum Theory, particularly entanglement. "Quantum like" experiments were undertaken on semantic space based on the Hyperspace Analogue Language (HAL) method. A quantum HAL model was implemented using state vectors issued from the HAL matrix and query observables, testing a wide range of windows sizes. The Bell parameter S, associating measures on two words in a document, was derived showing peaks for specific window sizes. The peaks show maximum quantum violation of the Bell inequalities and are document dependent. This new correlation measure inspired by Quantum Theory could be promising for measuring query relevance.
Abstract The possibilities of generating a contextual query using the quantum Hyperspace Analogue to Language (HAL) model are analyzed. An approach to establishing a semantic connection between words in texts is developed using the generally accepted basic formula for Bell’s parameter as a parameter of connection. A modification of the approach that allows determination of hyponymic isotopy and thus establish a semantic connection between the concepts is proposed. Prospects for using the quantum states of light to implement this approach are discussed.
This paper explores the potential of leveraging quantum entanglement for efficient computation and storage of semantic information, encompassing concepts and their relationships. The core claim is that utilizing quantum entanglement allows for parallel and distributed processing of semantic data, surpassing the limitations of classical computers in understanding and retrieving semantic information. The proposed mechanism involves encoding semantic information within entangled quantum states and manipulating these states through quantum gates to facilitate parallel computation and rapid exploration of complex relationships. This research represents a novel approach by integrating quantum computing with semantic understanding, offering a pathway to overcome traditional computational bottlenecks in semantic reasoning and information retrieval. The presented framework demonstrates a theoretical foundation for a new paradigm in information processing, focusing on exploiting quantum phenomena for enhanced semantic data manipulation. The key mathematical concepts and operations employed are outlined, providing a foundation for further research and development in this field. ---