Triple

T17143877
Position Surface form Disambiguated ID Type / Status
Subject Pulilan E416038 entity
Predicate countrySubdivisionName P2356 FINISHED
Object Bulacan 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: Bulacan | Statement: [Pulilan, countrySubdivisionName, Bulacan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bulacan
Context triple: [Pulilan, countrySubdivisionName, Bulacan]
  • A. Bulacan chosen
    Bulacan is a province in the Central Luzon region of the Philippines known for its historical significance, cultural heritage, and proximity to Metro Manila.
  • B. Pampanga
    Pampanga is a province in the Central Luzon region of the Philippines, known for its rich culinary heritage, vibrant festivals, and significant role in the country’s history and culture.
  • C. Nueva Vizcaya
    Nueva Vizcaya was a vast province of New Spain in northern Mexico that once encompassed areas now forming several modern states, including Durango.
  • D. Nueva Vizcaya
    Nueva Vizcaya is a landlocked province in the northern Philippines known for its mountainous terrain, agricultural economy, and ethnically diverse population.
  • E. Quezon Province
    Quezon Province is a coastal province in the Calabarzon region of Luzon in the Philippines, known for its coconut plantations, heritage towns, and access to the Pacific Ocean.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f2d8ca8c81909bba0cd6d60a4776 completed April 18, 2026, 9:08 p.m.
Created at: April 10, 2026, 5:36 a.m.