Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
named-entity-recognition
Languages:
Tagalog
Size:
1K - 10K
ArXiv:
DOI:
License:
File size: 1,817 Bytes
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title: "TLUnified-NER Corpus"
description: |
This dataset contains the annotated TLUnified corpora from Cruz and Cheng
(2021). It consists of a curated sample of around 7,000 documents for the
named entity recognition (NER) task. The majority of the corpus are news
reports in Tagalog, resembling the domain of the original ConLL 2003. There
are three entity types: Person (PER), Organization (ORG), and Location (LOC).
### About this repository
This repository is a [spaCy project](https://spacy.io/usage/projects) for
converting the annotated spaCy files into IOB. The process goes like this: we
download the raw corpus from Google Cloud Storage (GCS), convert the spaCy
files into a readable IOB format, and parse that using our loading script
(i.e., `tlunified-ner.py`). We're also shipping the IOB file so that it's
easier to access.
directories: ["assets", "corpus/spacy", "corpus/iob"]
vars:
version: 1.0
assets:
- dest: assets/corpus.tar.gz
description: "Annotated TLUnified corpora in spaCy format with train, dev, and test splits."
url: "https://storage.googleapis.com/ljvmiranda/calamanCy/tl_tlunified_gold/v${vars.version}/corpus.tar.gz"
workflows:
all:
- "setup-data"
- "upload-to-hf"
commands:
- name: "setup-data"
help: "Prepare the Tagalog corpora used for training various spaCy components"
script:
- mkdir -p corpus/spacy
- tar -xzvf assets/corpus.tar.gz -C corpus/spacy
- python -m spacy_to_iob corpus/spacy/ corpus/iob/
outputs:
- corpus/iob/train.iob
- corpus/iob/dev.iob
- corpus/iob/test.iob
- name: "upload-to-hf"
help: "Upload dataset to HuggingFace Hub"
script:
- git push
deps:
- corpus/iob/train.iob
- corpus/iob/dev.iob
- corpus/iob/test.iob
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