Triple

T10397911
Position Surface form Disambiguated ID Type / Status
Subject Misamis Oriental E245068 entity
Predicate hasMunicipality P847 FINISHED
Object Balingoan E821987 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: Balingoan | Statement: [Misamis Oriental, hasMunicipality, Balingoan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Balingoan
Context triple: [Misamis Oriental, hasMunicipality, Balingoan]
  • A. Balingoan chosen
    Balingoan is a coastal municipality in the Philippines known as a key ferry gateway to the island province of Camiguin.
  • B. Calbayog
    Calbayog is a coastal city in the province of Samar in the Philippines, known as a regional hub for trade, culture, and transportation in Eastern Visayas.
  • C. Argao
    Argao is a coastal municipality in the southeastern part of Cebu, Philippines, known for its Spanish-era heritage structures and traditional delicacies.
  • D. Kidapawan
    Kidapawan is a city in the Philippines that serves as the capital of Cotabato province on the island of Mindanao.
  • E. Balamban
    Balamban is a coastal municipality in the province of Cebu in the Philippines, known for its shipbuilding industry and growing economic zone.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9d0de448190b0bfd4d6c87d47fa completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d89f6fbc848190806d50bfad654b27 completed April 10, 2026, 6:57 a.m.
Created at: April 6, 2026, 12:07 p.m.