Triple

T5944338
Position Surface form Disambiguated ID Type / Status
Subject Orang Madura E132241 entity
Predicate diasporaRegion P10611 FINISHED
Object Jakarta E29483 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: Jakarta | Statement: [Orang Madura, diasporaRegion, Jakarta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jakarta
Context triple: [Orang Madura, diasporaRegion, Jakarta]
  • A. Jakarta chosen
    Jakarta is the bustling capital and largest city of Indonesia, serving as the country’s political, economic, and cultural center on the island of Java.
  • B. East Jakarta
    East Jakarta is one of the administrative cities of Indonesia’s capital, Jakarta, known for its mix of residential areas, industrial zones, and transportation hubs.
  • C. Bogor
    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.
  • D. 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.
  • E. Yogyakarta
    Yogyakarta is a major cultural and educational city on the Indonesian island of Java, renowned for its traditional arts, universities, and proximity to the Borobudur and Prambanan temples.
  • 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_69c00869d3308190af89b2453e0f7546 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03937b4a88190819a1fd63fc3d3ed completed March 22, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0bfe3d3d88190853f76e41c61ad71 completed March 23, 2026, 4:21 a.m.
Created at: March 22, 2026, 4:01 p.m.