Argument Linking: A Survey and Forecast

TL;DR

This paper surveys the field of argument linking in natural language understanding, highlighting its importance for information extraction and identifying key challenges and future directions in the area.

Contribution

It provides a comprehensive overview of existing approaches to argument linking and discusses their limitations to guide future research.

Findings

Identifies gaps in current argument linking methods

Highlights the importance of argument linking for NLU

Suggests future research directions

Abstract

Semantic role labeling (SRL) -- identifying the semantic relationships between a predicate and other constituents in the same sentence -- is a well-studied task in natural language understanding (NLU). However, many of these relationships are evident only at the level of the document, as a role for a predicate in one sentence may often be filled by an argument in a different one. This more general task, known as implicit semantic role labeling or argument linking, has received increased attention in recent years, as researchers have recognized its centrality to information extraction and NLU. This paper surveys the literature on argument linking and identifies several notable shortcomings of existing approaches that indicate the paths along which future research effort could most profitably be spent.