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UD_Naga-Suansu

Treebank card from UD release 2.18: metadata and texts come from UD_Naga-Suansu/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_Naga-Suansu; seeds: seeds/; converter: convert.md.

FieldValue
UD nameUD_Naga-Suansu
LanguageNaga (nmf)
FamilySino-Tibetan
Treebank codenmf_suansu
UD pageuniversaldependencies.org/treebanks/nmf suansu/index.html
LicenseCC BY-SA 4.0
Genresfiction, grammar-examples
Text in datayes
Parallelcairo
In UD sinceUD v2.16
AuthorsJessica K. Ivani; Kira Tulchynska
Contactjessica.ivani@uzh.ch; kira.tulchynska@mail.huji.ac.il
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
train2015615930
test5642 9422 964220
total5843 0983 123250

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

UD_Naga-Suansu is a Universal Dependencies (UD) treebank for Suansu (Glottocode: suan1234), an endangered Tibeto-Burman language spoken on the Indo-Myanmar border. The annotation was performed manually based on glosses. This treebank includes texts from fiction and grammar. The treebank contains 3.1k tokens, distributed as follows:

  • Training set: 2945 tokens
  • Test set: 157 tokens

Introduction

The UD_Naga-Suansu treebank consists of various texts translated into Suansu by native speakers, then glossed and annotated. The included texts are:

Genre Classification

  • Fiction: Sentence IDs start with film.
  • Grammar: Sentence IDs start with grammar.

Data Splits

  • Training set: Full grammar_Cairo
  • Test set: Full grammar_BivalTyp, grammar_ValPal, and film_Bridge

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