Who is the root in a syntactic dependency structure?

TL;DR

This paper investigates the properties of the root in syntactic dependency trees, proposing that root vertices are highly central, and introduces novel position-based scores to improve root identification.

Contribution

It introduces a new approach using position-based centrality scores to better identify the root in syntactic dependency structures, supported by theoretical and empirical analysis.

Findings

Root vertices tend to have high centrality scores.

Position-based scores outperform traditional methods in root prediction.

A network science perspective underpins the concept of rootness.

Abstract

The syntactic structure of a sentence can be described as a tree that indicates the syntactic relationships between words. In spite of significant progress in unsupervised methods that retrieve the syntactic structure of sentences, guessing the right direction of edges is still a challenge. As in a syntactic dependency structure edges are oriented away from the root, the challenge of guessing the right direction can be reduced to finding an undirected tree and the root. The limited performance of current unsupervised methods demonstrates the lack of a proper understanding of what a root vertex is from first principles. We consider an ensemble of centrality scores, some that only take into account the free tree (non-spatial scores) and others that take into account the position of vertices (spatial scores). We test the hypothesis that the root vertex is an important or central vertex of the syntactic dependency structure. We confirm the hypothesis in the sense that root vertices tend to have high centrality and that vertices of high centrality tend to be roots. The best performance in guessing the root is achieved by novel scores that only take into account the position of a vertex and that of its neighbours. We provide theoretical and empirical foundations towards a universal notion of rootness from a network science perspective.