Triple

T2734286
Position Surface form Disambiguated ID Type / Status
Subject Persebaya Surabaya E60591 entity
Predicate shortName P43 FINISHED
Object Persebaya E60591 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: Persebaya | Statement: [Persebaya Surabaya, shortName, Persebaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Persebaya
Context triple: [Persebaya Surabaya, shortName, Persebaya]
  • A. Persebaya Surabaya chosen
    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.
  • B. Gamba Osaka
    Gamba Osaka is a professional Japanese football club that competes in the J1 League and is known as one of the country's most successful and historic teams.
  • C. Vissel Kobe
    Vissel Kobe is a professional Japanese football club based in Kobe that competes in the J1 League.
  • D. Albirex Niigata
    Albirex Niigata is a professional Japanese football club based in Niigata that competes in the J.League.
  • E. Caps United F.C.
    Caps United F.C. is one of Zimbabwe’s most prominent football clubs, known for its passionate fan base and intense domestic rivalries.
  • 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_69ab4b77febc819095603eb012cd141b completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb0e7b888190bfa5d2e33f00ec0f completed March 7, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb6a15e548190a118880f9904f9cc completed March 10, 2026, 6:13 a.m.
Created at: March 6, 2026, 9:56 p.m.