Triple

T7009637
Position Surface form Disambiguated ID Type / Status
Subject Bogor Palace E162546 entity
Predicate near P350 FINISHED
Object Bogor city center E29215 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: Bogor city center | Statement: [Bogor Palace, near, Bogor city center]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bogor city center
Context triple: [Bogor Palace, near, Bogor city center]
  • A. Bogor chosen
    Bogor is a city on the Indonesian island of Java known for its cool climate, botanical gardens, and role as a major educational and research center.
  • B. Bogor Station
    Bogor Station is a major railway station and commuter rail terminus serving the city of Bogor and the greater Jakarta metropolitan area in Indonesia.
  • C. Pasar Gede
    Pasar Gede is a historic central market in Surakarta (Solo), Indonesia, known for its traditional Javanese architecture and wide variety of local foods and goods.
  • D. Senayan, Jakarta
    Senayan, Jakarta is a central district in Indonesia’s capital city known for its major government buildings, sports complex, and commercial centers.
  • E. North Jakarta
    North Jakarta is a coastal administrative city of Indonesia’s capital region, known for its busy port, industrial zones, and historic waterfront areas.
  • 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_69c6885928148190ae31909fbb5e9849 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc38039c8190ab420d62bb11b4d9 completed March 27, 2026, 7:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a47aa6481908ac0039b2b728edb completed March 28, 2026, 5:42 a.m.
Created at: March 27, 2026, 2:34 p.m.