Triple

T4703797
Position Surface form Disambiguated ID Type / Status
Subject Region XII E104339 entity
Predicate hasMunicipality P847 FINISHED
Object Midsayap E281926 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: Midsayap | Statement: [Region XII, hasMunicipality, Midsayap]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Midsayap
Context triple: [Region XII, hasMunicipality, Midsayap]
  • A. Midsayap chosen
    Midsayap is a first-class agricultural municipality in the province of North Cotabato on the island of Mindanao in the Philippines.
  • B. Maitum
    Maitum is a coastal municipality in the province of Sarangani in the Philippines, known for its archaeological sites and prehistoric anthropomorphic burial jars.
  • C. Mamburao
    Mamburao is a coastal municipality in the Philippines that serves as the capital of the province of Occidental Mindoro in the Mimaropa region.
  • D. Masbate
    Masbate is an island province in the central Philippines, known for its cattle ranches, rodeo festivals, and location between Luzon and the Visayas.
  • E. Binalong
    Binalong is a small rural village in New South Wales, Australia, known for its historic buildings and pastoral surroundings.
  • 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_69bd43e9b88481908582103dcadff3d9 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd63d082088190b7fc61a487d7ef2f completed March 20, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be03d074348190a19092fa02a0bb39 completed March 21, 2026, 2:34 a.m.
Created at: March 20, 2026, 1:17 p.m.