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

Yanai Elazar, Yoav Goldberg

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


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.

Original languageEnglish
Pages (from-to)519-535
Number of pages17
JournalTransactions of the Association for Computational Linguistics
StatePublished - 2019

Bibliographical note

Publisher Copyright:
© 2019 Association for Computational Linguistics. Distributed under a CC-BY 4.0 license.


We would like to thank Reut Tsarfaty and the Bar-Ilan University NLP lab for the fruitful conversation and helpful comments. The work was supported by the Israeli Science Foundation (grant 1555/15) and the German Research Foundation via the German-Israeli Project Cooperation (DIP, grant DA 1600/1-1).

FundersFunder number
DIPDA 1600/1-1
German-Israeli Project Cooperation
Reut Tsarfaty
Deutsche Forschungsgemeinschaft
Bar-Ilan University
Israel Science Foundation1555/15


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