Triple

T21975296
Position Surface form Disambiguated ID Type / Status
Subject Province of Bulacan E542689 entity
Predicate hasMunicipality P847 FINISHED
Object Angat 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: Angat | Statement: [Province of Bulacan, hasMunicipality, Angat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Angat
Context triple: [Province of Bulacan, hasMunicipality, Angat]
  • A. Angat chosen
    Angat is a landlocked municipality in the province of Bulacan in the Philippines, known for its river and proximity to the Angat Dam and watershed area.
  • B. Angat Dam
    Angat Dam is a major concrete water reservoir and hydroelectric facility in Bulacan, Philippines, that supplies much of Metro Manila’s potable water and power.
  • C. Angat River system
    The Angat River system is a major river network in Bulacan, Philippines, that supplies water, hydroelectric power, and irrigation to Metro Manila and surrounding provinces.
  • D. Bakun
    Bakun is a remote mountain municipality in the Philippine province of Benguet known for its rugged landscapes, waterfalls, and hiking trails.
  • E. Cagayan
    Cagayan is a province in the northeastern part of the Philippines known for its agricultural lands, coastal areas, and role as a regional center in Luzon.
  • 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_69e0c48070988190909db97667b9a0ac completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f12487a1a88190abb8a51fcd533b6a completed April 28, 2026, 9:20 p.m.
Created at: April 16, 2026, 8:03 p.m.