Triple

T16360639
Position Surface form Disambiguated ID Type / Status
Subject Guiguinto E397300 entity
Predicate borderedBy P224 FINISHED
Object Baliuag E413563 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: Baliuag | Statement: [Guiguinto, borderedBy, Baliuag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baliuag
Context triple: [Guiguinto, borderedBy, Baliuag]
  • A. Baliuag chosen
    Baliuag is a first-class municipality in the province of Bulacan in the Philippines, known as a commercial and educational hub in Central Luzon.
  • B. Cauayan
    Cauayan is a rapidly developing component city located in the province of Isabela in the Cagayan Valley region of the Philippines.
  • C. Dipaculao
    Dipaculao is a coastal municipality in the Philippine province of Aurora known for its beaches, surfing spots, and scenic mountain landscapes.
  • D. Abucay
    Abucay is a coastal municipality in the province of Bataan in the Philippines, known for its historical significance dating back to the Spanish colonial period.
  • E. Bansalan
    Bansalan is a municipality in the province of Davao del Sur in the Philippines, known for its agricultural economy and rural communities.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2fad304448190b3f6f0350a1e151d completed April 18, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00dbf46cf881909f6c16f7a3d9a535 completed May 10, 2026, 7:26 p.m.
Created at: April 10, 2026, 5:08 a.m.