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    <titleInfo>
        <title>Where’s My Head? Definition, Data Set, and Models for Numeric Fused-Head Identification and Resolution</title>
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    <name type="personal">
        <namePart type="given">Yanai</namePart>
        <namePart type="family">Elazar</namePart>
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    <abstract>We provide the first computational treatment of fused-heads constructions (FHs), focusing on the numeric fused-heads (NFHs). FHs constructions are noun phrases in which the head noun is missing and is said to be “fused” with its dependent modifier. This missing information is implicit and is important for sentence understanding. The missing references are easily filled in by humans but pose a challenge for computational models. We formulate the handling of FHs as a two stages process: Identification of the FH construction and resolution of the missing head. We explore the NFH phenomena in large corpora of English text and create (1) a data set and a highly accurate method for NFH identification; (2) a 10k examples (1 M tokens) crowd-sourced data set of NFH resolution; and (3) a neural baseline for the NFH resolution task. We release our code and data set, to foster further research into this challenging problem.</abstract>
    <identifier type="citekey">elazar-goldberg-2019-wheres</identifier>
    <identifier type="doi">10.1162/tacl_a_00280</identifier>
    <location>
        <url>https://aclanthology.org/Q19-1030</url>
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    <part>
        <date>2019</date>
        <detail type="volume"><number>7</number></detail>
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            <start>519</start>
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%0 Journal Article
%T Where’s My Head? Definition, Data Set, and Models for Numeric Fused-Head Identification and Resolution
%A Elazar, Yanai
%A Goldberg, Yoav
%J Transactions of the Association for Computational Linguistics
%D 2019
%V 7
%I MIT Press
%C Cambridge, MA
%F elazar-goldberg-2019-wheres
%X We provide the first computational treatment of fused-heads constructions (FHs), focusing on the numeric fused-heads (NFHs). FHs constructions are noun phrases in which the head noun is missing and is said to be “fused” with its dependent modifier. This missing information is implicit and is important for sentence understanding. The missing references are easily filled in by humans but pose a challenge for computational models. We formulate the handling of FHs as a two stages process: Identification of the FH construction and resolution of the missing head. We explore the NFH phenomena in large corpora of English text and create (1) a data set and a highly accurate method for NFH identification; (2) a 10k examples (1 M tokens) crowd-sourced data set of NFH resolution; and (3) a neural baseline for the NFH resolution task. We release our code and data set, to foster further research into this challenging problem.
%R 10.1162/tacl_a_00280
%U https://aclanthology.org/Q19-1030
%U https://doi.org/10.1162/tacl_a_00280
%P 519-535

Markdown (Informal)

[Where’s My Head? Definition, Data Set, and Models for Numeric Fused-Head Identification and Resolution](https://aclanthology.org/Q19-1030) (Elazar & Goldberg, TACL 2019)

• Where’s My Head? Definition, Data Set, and Models for Numeric Fused-Head Identification and Resolution (Elazar & Goldberg, TACL 2019)

ACL

• Yanai Elazar and Yoav Goldberg. 2019. Where’s My Head? Definition, Data Set, and Models for Numeric Fused-Head Identification and Resolution. Transactions of the Association for Computational Linguistics, 7:519–535.