Abstract

Semantic relations are often signaled with prepositional or possessive marking—but extreme polysemy bedevils their analysis and automatic interpretation. We introduce a new annotation scheme, corpus, and task for the disambiguation of prepositions and possessives in English. Unlike previous approaches, our annotations are comprehensive with respect to types and tokens of these markers; use broadly applicable supersense classes rather than fine-grained dictionary definitions; unite prepositions and possessives under the same class inventory; and distinguish between a marker’s lexical contribution and the role it marks in the context of a predicate or scene. Strong interannotator agreement rates, as well as encouraging disambiguation results with established supervised methods, speak to the viability of the scheme and task.

Highlights

  • Grammar, as per a common metaphor, gives speakers of a language a shared toolbox to construct and deconstruct meaningful and fluent utterances

  • Semantic interpretation requires some form of sense disambiguation, but arriving at a linguistic representation that is flexible enough to generalize across usages and types, yet simple enough to support reliable annotation, has been a daunting challenge (§2)

  • We argue for an approach to describing English preposition and possessive semantics with broad coverage

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Summary

Introduction

As per a common metaphor, gives speakers of a language a shared toolbox to construct and deconstruct meaningful and fluent utterances. The restaurant at in outside for/after an hour), to express configurational relationships like quantity, possession, part/whole, and membership (the coats of dozens of children in the class), and to indicate semantic roles in argument structure (Grandma cooked dinner for the children (1) I was booked for/DURATION 2 nights at/LOCUS this hotel in/TIME Oct 2007. The most recent class-based approach to prepositions was our initial framework of 75 preposition supersenses arranged in a multiple inheritance taxonomy (Schneider et al, 2015, 2016). It was based largely on relation/role inventories of Srikumar and Roth (2013) and VerbNet (Bonial et al, 2011; Palmer et al, 2017). Several limitations of our approach became clear to us over time

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