Constructing a Family Tree of Ten Indo-European Languages with Delexicalized Cross-linguistic Transfer Patterns

TL;DR

This paper constructs a phylogenetic tree of ten Indo-European languages by analyzing delexicalized transfer patterns derived from web data, linking historical divergence with second language acquisition constraints.

Contribution

It introduces a neural-based method to automatically induce interpretable transfer patterns, bridging historical linguistics and SLA insights with quantitative analysis.

Findings

Transfer patterns support historical divergence hypotheses

Delexicalized transfer aligns with phylogenetic structures

Neural methods effectively extract cross-linguistic transfer patterns

Abstract

It is reasonable to hypothesize that the divergence patterns formulated by historical linguists and typologists reflect constraints on human languages, and are thus consistent with Second Language Acquisition (SLA) in a certain way. In this paper, we validate this hypothesis on ten Indo-European languages. We formalize the delexicalized transfer as interpretable tree-to-string and tree-to-tree patterns which can be automatically induced from web data by applying neural syntactic parsing and grammar induction technologies. This allows us to quantitatively probe cross-linguistic transfer and extend inquiries of SLA. We extend existing works which utilize mixed features and support the agreement between delexicalized cross-linguistic transfer and the phylogenetic structure resulting from the historical-comparative paradigm.