metadata

license: gpl-3.0
task_categories:
  - token-classification
language:
  - tl
size_categories:
  - 1K<n<10K
pretty_name: TLUnified-NER
tags:
  - low-resource
  - named-entity-recognition

🪐 spaCy Project: Dataset builder to HuggingFace Hub

Dataset 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 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.

📋 project.yml

The project.yml defines the data assets required by the project, as well as the available commands and workflows. For details, see the spaCy projects documentation.

⏯ Commands

The following commands are defined by the project. They can be executed using spacy project run [name]. Commands are only re-run if their inputs have changed.

Command	Description
`setup-data`	Prepare the Tagalog corpora used for training various spaCy components
`upload-to-hf`	Upload dataset to HuggingFace Hub

⏭ Workflows

The following workflows are defined by the project. They can be executed using spacy project run [name] and will run the specified commands in order. Commands are only re-run if their inputs have changed.

Workflow	Steps
`all`	`setup-data` → `upload-to-hf`

🗂 Assets

The following assets are defined by the project. They can be fetched by running spacy project assets in the project directory.

File	Source	Description
`assets/corpus.tar.gz`	URL	Annotated TLUnified corpora in spaCy format with train, dev, and test splits.