[1811.03277v1] Towards Compositional Distributional Discourse Analysis
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Computer Science > Artificial Intelligence

arXiv:1811.03277v1 (cs)
[Submitted on 8 Nov 2018]

Title:Towards Compositional Distributional Discourse Analysis

Authors:Bob Coecke (University of Oxford), Giovanni de Felice (University of Oxford), Dan Marsden (University of Oxford), Alexis Toumi (University of Oxford)
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Abstract:Categorical compositional distributional semantics provide a method to derive the meaning of a sentence from the meaning of its individual words: the grammatical reduction of a sentence automatically induces a linear map for composing the word vectors obtained from distributional semantics. In this paper, we extend this passage from word-to-sentence to sentence-to-discourse composition. To achieve this we introduce a notion of basic anaphoric discourses as a mid-level representation between natural language discourse formalised in terms of basic discourse representation structures (DRS); and knowledge base queries over the Semantic Web as described by basic graph patterns in the Resource Description Framework (RDF). This provides a high-level specification for compositional algorithms for question answering and anaphora resolution, and allows us to give a picture of natural language understanding as a process involving both statistical and logical resources.
Comments: In Proceedings CAPNS 2018, arXiv:1811.02701
Subjects: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Databases (cs.DB)
Cite as: arXiv:1811.03277 [cs.AI]
  (or arXiv:1811.03277v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.1811.03277
Journal reference: EPTCS 283, 2018, pp. 1-12
Related DOI: https://doi.org/10.4204/EPTCS.283.1

Submission history

From: EPTCS [view email] [via EPTCS proxy]
[v1] Thu, 8 Nov 2018 05:14:19 UTC (22 KB)
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