Where’s My Head? Definition, Data Set, and Models for Numeric Fused-Head Identification and Resolution

Yanai Elazar, Yoav Goldberg


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.
Anthology ID:
Q19-1030
Volume:
Transactions of the Association for Computational Linguistics, Volume 7
Month:
March
Year:
2019
Address:
Venue:
TACL
SIG:
Publisher:
Note:
Pages:
519–535
Language:
URL:
https://www.aclweb.org/anthology/Q19-1030
DOI:
10.1162/tacl_a_00280
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PDF:
http://aclanthology.lst.uni-saarland.de/Q19-1030.pdf