The Linear Arrangement Library. A new tool for research on syntactic dependency structures

TL;DR

The paper introduces the Linear Arrangement Library (LAL), an open-source tool designed to facilitate the calculation of statistical metrics on syntactic dependency structures, promoting ease of use, reliability, and cross-disciplinary research.

Contribution

It presents a new, flexible, and thoroughly tested open-source library that simplifies the computation of dependency structure metrics for researchers of all programming levels.

Findings

LAL enables efficient calculation of dependency metrics.

The library is user-friendly and suitable for inexperienced programmers.

It unites research efforts across different traditions and regions.

Abstract

The new and growing field of Quantitative Dependency Syntax has emerged at the crossroads between Dependency Syntax and Quantitative Linguistics. One of the main concerns in this field is the statistical patterns of syntactic dependency structures. These structures, grouped in treebanks, are the source for statistical analyses in these and related areas; dozens of scores devised over the years are the tools of a new industry to search for patterns and perform other sorts of analyses. The plethora of such metrics and their increasing complexity require sharing the source code of the programs used to perform such analyses. However, such code is not often shared with the scientific community or is tested following unknown standards. Here we present a new open-source tool, the Linear Arrangement Library (LAL), which caters to the needs of, especially, inexperienced programmers. This tool enables the calculation of these metrics on single syntactic dependency structures, treebanks, and collection of treebanks, grounded on ease of use and yet with great flexibility. LAL has been designed to be efficient, easy to use (while satisfying the needs of all levels of programming expertise), reliable (thanks to thorough testing), and to unite research from different traditions, geographic areas, and research fields.