Triple

T4335015
Position Surface form Disambiguated ID Type / Status
Subject Calabarzon E97442 entity
Predicate hasCity P316 FINISHED
Object Bacoor E258205 NE FINISHED

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: Bacoor | Statement: [Calabarzon, hasCity, Bacoor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bacoor
Context triple: [Calabarzon, hasCity, Bacoor]
  • A. Bacoor chosen
    Bacoor is a coastal city in the province of Cavite in the Philippines, situated just south of Metro Manila along the shores of Manila Bay.
  • B. Kawit
    Kawit is a historic coastal municipality in the Philippine province of Cavite, best known as the site where Philippine independence from Spain was first proclaimed in 1898.
  • C. Palayan City
    Palayan City is a planned component city in the Philippines known for serving as the administrative and governmental center of the province of Nueva Ecija.
  • D. Batangas City
    Batangas City is a major port and industrial hub in the province of Batangas in the Philippines, known for its oil refineries, commercial activity, and role as a gateway to nearby islands.
  • E. Talisay City
    Talisay City is a coastal component city in the province of Cebu in the Philippines, known for its historical significance and proximity to Metro Cebu.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69b3454662a481908fbcd0bbfaa3a0a4 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35152bfc88190ab5d53ca38f98d8a completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4d66d4948190a095a92d0e3778ca completed March 21, 2026, 7:48 a.m.
Created at: March 12, 2026, 11:14 p.m.