{"url":"/dataset/tlunified-ner","name":"TLUnified-NER","full_name":null,"description_markdown":"We present the development of a Named Entity Recognition (NER) dataset for Tagalog. This corpus helps fill the resource gap present in Philippine languages today, where NER resources are scarce. The texts were obtained from a pretraining corpora containing news reports, and were labeled by native speakers in an iterative fashion. The resulting dataset contains ~7.8k documents across three entity types: Person, Organization, and Location. The inter-annotator agreement, as measured by Cohen's κ, is 0.81. We also conducted extensive empirical evaluation of state-of-the-art methods across supervised and transfer learning settings. Finally, we released the data and processing code publicly to inspire future work on Tagalog NLP.","description_withheld":null,"homepage":"https://huggingface.co/datasets/ljvmiranda921/tlunified-ner","introduced_date":"2023-11-13","introduced_date_note":null,"introduced_by":{"paper":"/paper/developing-a-named-entity-recognition-dataset","title":"Developing a Named Entity Recognition Dataset for Tagalog","first_author":"Lester James V. Miranda","url":null},"license":{"name":"GNU GPL v3","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"NER","url":"/task/cg","datasets_with_task":"/datasets/task/cg"}],"languages":[{"name":"Tagalog","url":"/datasets/language/tagalog"}],"variants":["TLUnified-NER"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}