Triple

T12444359
Position Surface form Disambiguated ID Type / Status
Subject Persija Jakarta E297357 entity
Predicate shortName P43 FINISHED
Object Persija E297357 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: Persija | Statement: [Persija Jakarta, shortName, Persija]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Persija
Context triple: [Persija Jakarta, shortName, Persija]
  • A. Persija Jakarta chosen
    Persija Jakarta is a prominent professional football club based in Jakarta, Indonesia, known for its large fanbase and historic status in Indonesian football.
  • B. Persebaya Surabaya
    Persebaya Surabaya is a prominent Indonesian professional football club based in Surabaya, East Java, known for its passionate fan base and success in domestic competitions.
  • C. Arema FC
    Arema FC is a professional Indonesian football club based in Malang, East Java, known for its passionate fanbase and fierce derbies against Persebaya Surabaya.
  • D. PSIS Semarang
    PSIS Semarang is an Indonesian professional football club based in Semarang, Central Java, known for its passionate fanbase and historic presence in the national league system.
  • E. Arema
    Arema is a French company that manages and operates major sports and events venues, including Marseille’s Stade Vélodrome.
  • 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_69f746055aac81909626eaa891199019 completed May 3, 2026, 12:56 p.m.
Created at: April 8, 2026, 9:55 p.m.