Triple

T6780461
Position Surface form Disambiguated ID Type / Status
Subject Tanah Kusir Cemetery E155667 entity
Predicate locatedIn P40 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: [Tanah Kusir Cemetery, locatedIn, Jakarta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jakarta
Context triple: [Tanah Kusir Cemetery, locatedIn, 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. 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. 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.
  • D. 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.
  • 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_69c688162bf8819088b664b5c3b5be7a completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d26b32c0819093f86b1002260660 completed March 27, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712aa0b148190955c58af69849cc4 completed March 27, 2026, 11:28 p.m.
Created at: March 27, 2026, 2:14 p.m.