Triple

T13293722
Position Surface form Disambiguated ID Type / Status
Subject Pinrang Regency E316623 entity
Predicate capital P234 FINISHED
Object Pinrang E316623 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: Pinrang | Statement: [Pinrang Regency, capital, Pinrang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pinrang
Context triple: [Pinrang Regency, capital, Pinrang]
  • A. Pinrang Regency chosen
    Pinrang Regency is an administrative region on the western coast of South Sulawesi, Indonesia, known for its agricultural activities and coastal landscapes.
  • B. Parepare
    Parepare is a coastal city and important port on the western coast of South Sulawesi, Indonesia.
  • C. Sipalay
    Sipalay is a coastal city in Negros Occidental, Philippines, known for its beaches, diving spots, and laid-back tourism.
  • D. Dipolog
    Dipolog is a coastal city in the Zamboanga Peninsula region of the southern Philippines, known as the "Bottled Sardines Capital of the Philippines."
  • E. Balanga City
    Balanga City is a component city in the province of Bataan, Philippines, known for its historical significance in World War II and its role as the provincial capital.
  • 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99078bcf0819083195fb556bcacb2 completed April 11, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716d8ee2081908428339216c43b47 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:28 p.m.