<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="dorr-voss-2018-case">
    <titleInfo>
        <title>The Case for Systematically Derived Spatial Language Usage</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Bonnie</namePart>
        <namePart type="family">Dorr</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Clare</namePart>
        <namePart type="family">Voss</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2018-06</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the First International Workshop on Spatial Language Understanding</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Parisa</namePart>
            <namePart type="family">Kordjamshidi</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Archna</namePart>
            <namePart type="family">Bhatia</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">James</namePart>
            <namePart type="family">Pustejovsky</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Marie-Francine</namePart>
            <namePart type="family">Moens</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">New Orleans</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>This position paper argues that, while prior work in spatial language understanding for tasks such as robot navigation focuses on mapping natural language into deep conceptual or non-linguistic representations, it is possible to systematically derive regular patterns of spatial language usage from existing lexical-semantic resources. Furthermore, even with access to such resources, effective solutions to many application areas such as robot navigation and narrative generation also require additional knowledge at the syntax-semantics interface to cover the wide range of spatial expressions observed and available to natural language speakers. We ground our insights in, and present our extensions to, an existing lexico-semantic resource, covering 500 semantic classes of verbs, of which 219 fall within a spatial subset. We demonstrate that these extensions enable systematic derivation of regular patterns of spatial language without requiring manual annotation.</abstract>
    <identifier type="citekey">dorr-voss-2018-case</identifier>
    <identifier type="doi">10.18653/v1/W18-1408</identifier>
    <location>
        <url>https://aclanthology.org/W18-1408</url>
    </location>
    <part>
        <date>2018-06</date>
        <extent unit="page">
            <start>63</start>
            <end>70</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T The Case for Systematically Derived Spatial Language Usage
%A Dorr, Bonnie
%A Voss, Clare
%Y Kordjamshidi, Parisa
%Y Bhatia, Archna
%Y Pustejovsky, James
%Y Moens, Marie-Francine
%S Proceedings of the First International Workshop on Spatial Language Understanding
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans
%F dorr-voss-2018-case
%X This position paper argues that, while prior work in spatial language understanding for tasks such as robot navigation focuses on mapping natural language into deep conceptual or non-linguistic representations, it is possible to systematically derive regular patterns of spatial language usage from existing lexical-semantic resources. Furthermore, even with access to such resources, effective solutions to many application areas such as robot navigation and narrative generation also require additional knowledge at the syntax-semantics interface to cover the wide range of spatial expressions observed and available to natural language speakers. We ground our insights in, and present our extensions to, an existing lexico-semantic resource, covering 500 semantic classes of verbs, of which 219 fall within a spatial subset. We demonstrate that these extensions enable systematic derivation of regular patterns of spatial language without requiring manual annotation.
%R 10.18653/v1/W18-1408
%U https://aclanthology.org/W18-1408
%U https://doi.org/10.18653/v1/W18-1408
%P 63-70

Markdown (Informal)

[The Case for Systematically Derived Spatial Language Usage](https://aclanthology.org/W18-1408) (Dorr & Voss, SpLU 2018)

• The Case for Systematically Derived Spatial Language Usage (Dorr & Voss, SpLU 2018)

ACL

• Bonnie Dorr and Clare Voss. 2018. The Case for Systematically Derived Spatial Language Usage. In Proceedings of the First International Workshop on Spatial Language Understanding, pages 63–70, New Orleans. Association for Computational Linguistics.