Triple

T12252514
Position Surface form Disambiguated ID Type / Status
Subject Bonek E292008 entity
Predicate associatedClubNickname P5076 FINISHED
Object Bajul Ijo E292005 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: Bajul Ijo | Statement: [Bonek, associatedClubNickname, Bajul Ijo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bajul Ijo
Context triple: [Bonek, associatedClubNickname, Bajul Ijo]
  • A. Bajul Ijo chosen
    Bajul Ijo is the popular nickname of Indonesian football club Persebaya Surabaya, reflecting its green colors and crocodile-themed identity.
  • B. Jajau
    Jajau is a locality in northern India historically noted as the place where the Mughal prince Azam Shah died.
  • C. Ranu Pakis
    Ranu Pakis is a volcanic crater lake in East Java, Indonesia, known for its scenic setting near Mount Lamongan.
  • D. Bayabas
    Bayabas is a coastal municipality in the Philippine province of Surigao del Sur known for its fishing communities and rural seaside landscapes.
  • E. Gelgel
    Gelgel is a historic village in Bali, Indonesia, known as a former royal capital and cultural center of the Klungkung kingdom.
  • 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_69d6ab67950c8190be08450a06228c4b completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cc849308190b6ff416f8b4f01e8 completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60abdc5988190a19104385f54fb06 completed May 2, 2026, 2:31 p.m.
Created at: April 8, 2026, 9:52 p.m.