Triple

T23368481
Position Surface form Disambiguated ID Type / Status
Subject Oroko E593391 entity
Predicate hasSubgroup P747 FINISHED
Object Bima 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: Bima | Statement: [Oroko, hasSubgroup, Bima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bima
Context triple: [Oroko, hasSubgroup, Bima]
  • A. Bima chosen
    Bima is a coastal city on the eastern part of Sumbawa Island in Indonesia, known as a regional hub for trade and culture in West Nusa Tenggara.
  • B. Bima
    Bima is a powerful and virtuous warrior hero from the Indian epic Mahabharata, renowned for his immense strength and fierce loyalty to his family.
  • C. Dipatiukur
    Dipatiukur is a central urban area in Bandung, Indonesia, known for hosting one of Universitas Padjadjaran’s main campuses and its surrounding student-oriented neighborhood.
  • D. Blitar
    Blitar is a city in East Java, Indonesia, best known as the hometown and final resting place of the country’s first president, Sukarno.
  • E. Sukaraja
    Sukaraja is a district in Bogor Regency, West Java, Indonesia, known as a suburban area supporting the greater Bogor and Jakarta regions.
  • 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_69e25d2593c88190bcdf4a716a94ccb2 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1a0aed374819097d38f51894bee44 completed April 29, 2026, 6:09 a.m.
Created at: April 17, 2026, 5:32 p.m.