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

By Yanai Elazar, Yoav Goldberg. 2019

25 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence, Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Natural Language Processing

Citations in the corpus

oLMpics-On What Language Model Pre-training Captures (2019, background): “The sentence also contains nominal ellipsis, also known as fused-heads (Elazar and Goldberg, 2019).”
Representing Numbers in NLP: a Survey and a Vision (2021, unknown): “For example, the sentence “ I woke up at 11 " has ‘a.m.’ or ‘o’clock’ as the fused head to be resolved (Elazar and Goldberg, 2019).”