Triple

T7788976
Position Surface form Disambiguated ID Type / Status
Subject Cipinang E187323 entity
Predicate locatedIn P40 FINISHED
Object East Jakarta E198448 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: East Jakarta | Statement: [Cipinang, locatedIn, East Jakarta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: East Jakarta
Context triple: [Cipinang, locatedIn, East Jakarta]
  • A. East Jakarta chosen
    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.
  • B. West Jakarta
    West Jakarta is a densely populated administrative city of Jakarta, Indonesia, known for its mix of residential areas, commercial centers, and historical sites.
  • C. 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.
  • D. South Jakarta
    South Jakarta is a municipality in the southern part of Indonesia’s capital region, known for its upscale residential areas, business districts, and shopping and entertainment centers.
  • E. Central Jakarta
    Central Jakarta is the administrative and political heart of Indonesia’s capital city, encompassing key government institutions, historic landmarks, and major commercial districts.
  • 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_69ca82af2d2c8190963861f5e0b8bf21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cae7e8a0d08190b6d4ca560681eb35 completed March 30, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb139fdf188190b1c80dd6d008c34d completed March 31, 2026, 12:21 a.m.
Created at: March 30, 2026, 4:25 p.m.