Named Graphs for Semantic Representation

Proceedings of the 7th Joint Conference on Lexical and Computational Semantics (*SEM), pages 113–118 New Orleans, June 5-6, 2018. c⃝2018 Association for Computational Linguistics Named Graphs for Semantic Representations Richard Crouch A9.com dick.crouch@gmail.com Aikaterini-Lida Kalouli University of Konstanz aikaterini-lida.kalouli@uni-konstanz.de Abstract A position paper arguing that purely graphical representations for natural language semantics lack a fundamental degree of expressiveness, and cannot deal with even basic Boolean op- erations like negation or disjunction, let alone intensional phenomena. Moving from graphs to named graphs leads to representations that stand some chance of having sufficient expres- sive power. Named FL0 graphs are of partic- ular interest. 1 Introduction Graphs are popular for both (semantic web) knowledge representation (Screiber and Raimond, 2014; Dong et al., 2014; Rospocher et al., 2016) and natural language semantics (Banarescu et al., 2013; Perera et al., 2018; Wities et al., 2017). The casual observer might assume there is substantial overlap between the two activities, but there is less than meets the eye. This paper attempts to make three points: 1. Knowledge graphs, which are designed to represent facts about the world rather than human knowledge, are not well set up to represent nega- tion, disjunction, and conditional or hypothetical contexts. Arguably, the world contains no nega- tive, disjunctive, or hypothetical facts; just posi- tive facts that make them true. Natural language semantics has to deal with more partial assertions, where all that is known are the negations, dis- junctions, or hypotheticals, and not the underlying facts that make them true. 2. Named graphs (Carroll et al., 2005) are an extension of RDF graphs (Screiber and Raimond, 2014), primarily introduced to record provenance information. They are worthy of further study, since they promise a way of bridging between the relentlessly positive world of knowledge represen- tation and the more partial, hypothetical world of natural language. In RDF-OWL graphs (Hitzler et al., 2012), the subject-predicate-object triples forming the nodes and arcs of the graph corre- spond to atomic propositions. Beyond conjunc- tion, no direct relations between these proposi- tions can be expressed. Named graphs allow sub- graphs (i.e. collections of atomic propositions) to be placed in relationships with other sub-graphs, and thus allow for negative, disjunctive and hypo- thetical relations between complex propositions. 3. Named graphs illustrate a certain way of factoring out complexity, in this case between predicate-argument structure and Boolean / modal structure. As a semantic representation, the predicate-argument structure is correct, but not complete. Adding a named, Boolean layer re- quires no adjustment to the syntax or semantics of the predicate-argument structure; it just embeds it in a broader environment. This often is not the case; e.g. in moving from unquantified predicate logic to first-order quantified logic, to first-oder modal logic, to higher-order intensional logic. After reviewing RDF graphs and named graphs, we discuss how they could be applied to a (some- what incestuous) family of layered, graphical, se- mantic representations (Boston et al., forthcom- ing; Shen et al., 2018; Bobrow et al., 2007) (see our companion paper (Kalouli …

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