SOTAVerified

RNN Simulations of Grammaticality Judgments on Long-distance Dependencies

2018-08-01COLING 2018Code Available0· sign in to hype

Shammur Absar Chowdhury, Roberto Zamparelli

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

The paper explores the ability of LSTM networks trained on a language modeling task to detect linguistic structures which are ungrammatical due to extraction violations (extra arguments and subject-relative clause island violations), and considers its implications for the debate on language innatism. The results show that the current RNN model can correctly classify (un)grammatical sentences, in certain conditions, but it is sensitive to linguistic processing factors and probably ultimately unable to induce a more abstract notion of grammaticality, at least in the domain we tested.

Tasks

Reproductions