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    <titleInfo>
        <title>Building Analyses from Syntactic Inference in Local Languages: An HPSG Grammar Inference System</title>
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    <name type="personal">
        <namePart type="given">Kristen</namePart>
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    <abstract>We present a grammar inference system that leverages linguistic knowledge recorded in the form of annotations in interlinear glossed text (IGT) and in a meta-grammar engineering system (the LinGO Grammar Matrix customization system) to automatically produce machine-readable HPSG grammars. Building on prior work to handle the inference of lexical classes, stems, affixes and position classes, and preliminary work on inferring case systems and word order, we introduce an integrated grammar inference system that covers a wide range of fundamental linguistic phenomena. System development was guided by 27 geneologically and geographically diverse languages, and we test the system‘s cross-linguistic generalizability on an additional 5 held-out languages, using datasets provided by field linguists. Our system out-performs three baseline systems in increasing coverage while limiting ambiguity and producing richer semantic representations, while also producing richer representations than previous work in grammar inference.</abstract>
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    <identifier type="doi">10.3384/nejlt.2000-1533.2022.4017</identifier>
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%0 Journal Article
%T Building Analyses from Syntactic Inference in Local Languages: An HPSG Grammar Inference System
%A Howell, Kristen
%A Bender, Emily M.
%J Northern European Journal of Language Technology
%D 2022
%V 8
%I Linköping University Electronic Press
%C Linköping, Sweden
%F howell-bender-2022-building
%X We present a grammar inference system that leverages linguistic knowledge recorded in the form of annotations in interlinear glossed text (IGT) and in a meta-grammar engineering system (the LinGO Grammar Matrix customization system) to automatically produce machine-readable HPSG grammars. Building on prior work to handle the inference of lexical classes, stems, affixes and position classes, and preliminary work on inferring case systems and word order, we introduce an integrated grammar inference system that covers a wide range of fundamental linguistic phenomena. System development was guided by 27 geneologically and geographically diverse languages, and we test the system‘s cross-linguistic generalizability on an additional 5 held-out languages, using datasets provided by field linguists. Our system out-performs three baseline systems in increasing coverage while limiting ambiguity and producing richer semantic representations, while also producing richer representations than previous work in grammar inference.
%R 10.3384/nejlt.2000-1533.2022.4017
%U https://aclanthology.org/2022.nejlt-1.3/
%U https://doi.org/10.3384/nejlt.2000-1533.2022.4017

Markdown (Informal)

[Building Analyses from Syntactic Inference in Local Languages: An HPSG Grammar Inference System](https://aclanthology.org/2022.nejlt-1.3/) (Howell & Bender, NEJLT 2022)

• Building Analyses from Syntactic Inference in Local Languages: An HPSG Grammar Inference System (Howell & Bender, NEJLT 2022)

ACL

• Kristen Howell and Emily M. Bender. 2022. Building Analyses from Syntactic Inference in Local Languages: An HPSG Grammar Inference System. Northern European Journal of Language Technology, 8.