Triple

T19031691
Position Surface form Disambiguated ID Type / Status
Subject La Union E465754 entity
Predicate hasMunicipality P847 FINISHED
Object Bangar NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Bangar | Statement: [La Union, hasMunicipality, Bangar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bangar
Context triple: [La Union, hasMunicipality, Bangar]
  • A. Bangar chosen
    Bangar is a coastal municipality in the province of La Union in the Philippines, known for its handwoven textiles and agricultural products.
  • B. Bogangar
    Bogangar is a coastal village in northern New South Wales, Australia, known for its proximity to Cabarita Beach and its relaxed seaside lifestyle.
  • C. Bangana
    Bangana is a town in the Una district of Himachal Pradesh, India, known as a local commercial and administrative center for the surrounding rural area.
  • D. Baner
    Baner is a rapidly developing residential and commercial suburb in the western part of Pune, Maharashtra, known for its IT offices, eateries, and proximity to major tech hubs.
  • E. Bangan
    Bangan is a barangay (village-level administrative division) of the municipality of Botolan in the province of Zambales, Philippines.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8dd0359648190bc2a9202c5cf29d2 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d7410dd08190b08a7c0a2b8d67f3 completed April 20, 2026, 7:35 a.m.
Created at: April 10, 2026, 12:02 p.m.