UD_Romanian-SiMoNERo
Treebank card from UD release 2.18: metadata and texts come from UD_Romanian-SiMoNERo/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_Romanian-SiMoNERo; seeds: seeds/; converter: convert.md.
| Field | Value |
|---|---|
| UD name | UD_Romanian-SiMoNERo |
| Language | Romanian (ro) |
| Family | IE |
| Treebank code | ro_simonero |
| UD page | universaldependencies.org/treebanks/ro simonero/index.html |
| License | CC BY-SA 4.0 |
| Genres | medical |
| Text in data | yes |
| Parallel | no |
| In UD since | UD v2.5 |
| Authors | Maria Mitrofan; Verginica Barbu Mititelu |
| Contact | maria@racai.ro, vergi@racai.ro |
| Development | outside the UD repo (elsewhere): fixes go to the source or the converter |
Annotation layers
| Layer | Origin |
|---|---|
| Lemmas | converted from manual |
| UPOS | converted from manual |
| XPOS | manual native |
| Features | converted from manual |
| Relations | converted from manual |
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
| Split | Sentences | Tokens | Words | Multiword tokens | Empty nodes |
|---|---|---|---|---|---|
| train | 3 747 | 116 857 | 116 857 | 0 | 0 |
| dev | 443 | 14 611 | 14 611 | 0 | 0 |
| test | 491 | 14 552 | 14 552 | 0 | 0 |
| total | 4 681 | 146 020 | 146 020 | 0 | 0 |
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.
Summary
SiMoNERo is a medical corpus of contemporary Romanian.
Introduction
SiMoNERo contains texts from three medical subdomains: cardiology, diabetes, endocrinology. The texts come from scientific books, journal articles and blog posts, but predominant are those coming from books. The texts display the following levels of annotation: tokenization, POS tagging, lemmatization, syntactic parsing and medical Named Entities (of the following types: ANAT (body parts), CHEM (Chemicals and Drugs), DISO (disorders), and PROC (procedures)). All levels, except for the syntactic one, are hand validated. The description of the corpus creation (excluding the syntactic annotation) is presented in Mitrofan et al. (2019). The syntactic parsing was made with the NLP Cube (github.com/adobe/NLP-Cube) system.
This page in Markdown → https://md.mova.elamur.ai/free/en/docs/treebanks/ro/simonero/