Triple

T13864778
Position Surface form Disambiguated ID Type / Status
Subject Sinjai Regency E333294 entity
Predicate capital P234 FINISHED
Object Sinjai E333294 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: Sinjai | Statement: [Sinjai Regency, capital, Sinjai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sinjai
Context triple: [Sinjai Regency, capital, Sinjai]
  • A. Sinjai Regency chosen
    Sinjai Regency is an administrative region in Indonesia known for its coastal landscapes, agricultural activities, and cultural diversity within the province of South Sulawesi.
  • B. Payakumbuh
    Payakumbuh is a city in West Sumatra, Indonesia, known as an important hub of Minangkabau culture, cuisine, and traditional arts.
  • C. Sidrap Regency
    Sidrap Regency is an administrative region in South Sulawesi, Indonesia, known for its agricultural activities and location in the island’s central area.
  • D. Tondano
    Tondano is a town in North Sulawesi, Indonesia, known as an administrative and cultural center of the Minahasa region near Lake Tondano.
  • E. Makasar
    Makasar is a district in East Jakarta, Indonesia, known as a primarily residential and urban area within the capital’s eastern region.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de05c30d9c81908217d41a3b4aaf85 completed April 14, 2026, 9:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd192b5e508190b2d385657f9e358f completed May 7, 2026, 10:58 p.m.
Created at: April 9, 2026, 10:14 p.m.