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UD_Zaar-Autogramm

Treebank card from UD release 2.18: metadata and texts come from UD_Zaar-Autogramm/README.md; size is counted by streaming the .conllu files and checked against the release stats.xml. Generated by tools/treebanks build; do not edit by hand. Papers: Papers: UD_Zaar-Autogramm; seeds: seeds/; converter: convert.md.

FieldValue
UD nameUD_Zaar-Autogramm
LanguageZaar (say)
FamilyAfro-Asiatic
Treebank codesay_autogramm
UD pageuniversaldependencies.org/treebanks/say autogramm/index.html
LicenseCC BY-SA 4.0
Genresgrammar-examples
Text in datayes
Parallelno
In UD sinceUD v2.11
AuthorsSylvain Kahane; Bruno Guillaume; Bernard Caron; Katharine Jiang
Contactbruno.guillaume@inria.fr
Developmentin the UD repo (here)

Annotation layers

LayerOrigin
Lemmasmanual native
UPOSmanual native
XPOSnot available
Featuresmanual native
Relationsmanual native

UD scale: manual native — annotated by hand directly in UD; converted from manual — converted from manual annotation in another scheme; converted with corrections — converted and partly corrected by hand; automatic with corrections — automatic, with partial manual corrections; automatic — automatic; not available — the layer is absent.

Size

SplitSentencesTokensWordsMultiword tokensEmpty nodes
train97810 10310 7125560
test1 1279 52610 2406540
total2 10519 62920 9521 2100

Tokens are surface tokens (Spanish vámonos is one), words are syntactic words (vamos + nos); multiword tokens are those split into several words; empty nodes are the N.M nodes of the enhanced graph. Splits dev are absent from the release.

Summary

A Universal Dependencies corpus for Zaar (aka Sayanci), a member of the Chadic branch of the Afro-Asiatic phylum. The language is mainly spoken by about 200,000 speakers in the Bogoro and Tafawa Balewa local governments of Bauchi State, Nigeria.

Introduction

The treebank is an automatic conversion of the SUD_Zaar-Autogramm, which was extracted from Bernard Caron's corpus in Elan format (corpafroas.huma-num.fr/Archives/corpus.php).

Sentences are annotated with the following metadata:

  • sent_id (which indicates the source file and the segmentation identifier in the source file)
  • speaker_id (which identifies the turn of speech)
  • sound_url (which enables playback of the audio recording)
  • seṅt_timecode (which enables playback of the sentence)
  • text (lexical tokenization)
  • text_ortho (original transcription of the audio recording)
  • text_en (English interpretation)

This page in Markdown → https://md.mova.elamur.ai/free/en/docs/treebanks/say/autogramm/