Triple

T12444357
Position Surface form Disambiguated ID Type / Status
Subject Persija Jakarta E297357 entity
Predicate homeCity P263 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: [Persija Jakarta, homeCity, Jakarta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jakarta
Context triple: [Persija Jakarta, homeCity, 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d8fd9848190a83410353d88ea8d completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64b9d34848190b02311ada2572440 completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:55 p.m.