Triple

T20069539
Position Surface form Disambiguated ID Type / Status
Subject Province of Quezon E499696 entity
Predicate hasMunicipality P847 FINISHED
Object Mauban 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: Mauban | Statement: [Province of Quezon, hasMunicipality, Mauban]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mauban
Context triple: [Province of Quezon, hasMunicipality, Mauban]
  • A. Mauban chosen
    Mauban is a coastal municipality in the province of Quezon, Philippines, known for its port, fishing industry, and access to nearby islands and natural attractions.
  • B. Narvacan
    Narvacan is a coastal municipality in the province of Ilocos Sur in the Philippines, known for its historic churches, scenic beaches, and wind-swept landscapes.
  • C. Koronadal
    Koronadal is a city in the Philippines that serves as the capital of South Cotabato and the regional administrative center of Soccsksargen.
  • D. Balamban
    Balamban is a coastal municipality in the province of Cebu in the Philippines, known for its shipbuilding industry and growing economic zone.
  • E. Malapatan
    Malapatan is a coastal municipality in the province of Sarangani in the Philippines, known for its diverse indigenous communities and agricultural economy.
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e664365ad0819089103b00d1cf8c9f completed April 20, 2026, 5:36 p.m.
Created at: April 11, 2026, 3:39 p.m.