How Universal is Genre in Universal Dependencies?

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Abstract

This work provides the first in-depth analysis of genre in Universal Dependencies (UD). In contrast to prior work on genre identification which uses small sets of well-defined labels in mono-/bilingual setups, UD contains 18 genres with varying degrees of specificity spread across 114 languages. As most treebanks are labeled with multiple genres while lacking annotations about which instances belong to which genre, we propose four methods for predicting instance-level genre using weak supervision from treebank metadata. The proposed methods recover instance-level genre better than competitive baselines as measured on a subset of UD with labeled instances and adhere better to the global expected distribution. Our analysis sheds light on prior work using UD genre metadata for treebank selection, finding that metadata alone are a noisy signal and must be disentangled within treebanks before it can be universally applied.
OriginalsprogEngelsk
TitelProceedings of the 20th International Workshop on Treebanks and Linguistic Theories (TLT, SyntaxFest 2021)
UdgivelsesstedSofia, Bulgaria
ForlagAssociation for Computational Linguistics
Publikationsdatodec. 2021
Sider69-85
StatusUdgivet - dec. 2021
Begivenhed20th International Workshop on Treebanks and Linguistic Theories (TLT, SyntaxFest 2021) - Sofia, Bulgarien
Varighed: 21 mar. 202225 mar. 2022
Konferencens nummer: 20

Workshop

Workshop20th International Workshop on Treebanks and Linguistic Theories (TLT, SyntaxFest 2021)
Nummer20
Land/OmrådeBulgarien
BySofia
Periode21/03/202225/03/2022

Emneord

  • Universal Dependencies
  • Genre Identification
  • Treebank Metadata
  • Weak Supervision
  • Instance-level Prediction

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