English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  On the distribution of deep clausal embeddings: a large Cross-linguistic Study

Blasi, D. E., Cotterell, R., Wolf-Sonkin, L., Stoll, S., Bickel, B., & Baroni, M. (2019). On the distribution of deep clausal embeddings: a large Cross-linguistic Study. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (pp. 3938-3943). Florence, Italy: Association for Computational Linguistics. Retrieved from https://www.aclweb.org/anthology/P19-1384.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/21.11116/0000-0004-628D-F Version Permalink: http://hdl.handle.net/21.11116/0000-0004-628E-E
Genre: Conference Paper

Files

show Files
hide Files
:
shh2341.pdf (Publisher version), 816KB
 
File Permalink:
-
Name:
shh2341.pdf
Description:
-
Visibility:
Private
MIME-Type / Checksum:
application/pdf
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Blasi, Damián E.1, Author              
Cotterell, Ryan, Author
Wolf-Sonkin, Lawrence, Author
Stoll, Sabine, Author
Bickel, Balthasar, Author
Baroni, Marco, Author
Affiliations:
1Linguistic and Cultural Evolution, Max Planck Institute for the Science of Human History, Max Planck Society, ou_2074311              

Content

show
hide
Free keywords: -
 Abstract: Embedding a clause inside another (``}the girl [who likes cars [that run fast]] has arrived{'') is a fundamental resource that has been argued to be a key driver of linguistic expressiveness. As such, it plays a central role in fundamental debates on what makes human language unique, and how they might have evolved. Empirical evidence on the prevalence and the limits of embeddings has however been based on either laboratory setups or corpus data of relatively limited size. We introduce here a collection of large, dependency-parsed written corpora in 17 languages, that allow us, for the first time, to capture clausal embedding through dependency graphs and assess their distribution. Our results indicate that there is no evidence for hard constraints on embedding depth: the tail of depth distributions is heavy. Moreover, although deeply embedded clauses tend to be shorter, suggesting processing load issues, complex sentences with many embeddings do not display a bias towards less deep embeddings. Taken together, the results suggest that deep embeddings are not disfavoured in written language. More generally, our study illustrates how resources and methods from latest-generation big-data NLP can provide new perspectives on fundamental questions in theoretical linguistics.

Details

show
hide
Language(s): eng - English
 Dates: 2019-072019-07
 Publication Status: Published in print
 Pages: 6
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: Other: shh2341
URI: https://www.aclweb.org/anthology/P19-1384
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Florence, Italy : Association for Computational Linguistics
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 3938 - 3943 Identifier: -