Triple

T22835882
Position Surface form Disambiguated ID Type / Status
Subject municipal government of Probolinggo E565945 entity
Predicate locatedIn P40 FINISHED
Object Probolinggo NE NERFINISHED

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: Probolinggo | Statement: [municipal government of Probolinggo, locatedIn, Probolinggo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Probolinggo
Context triple: [municipal government of Probolinggo, locatedIn, Probolinggo]
  • A. Probolinggo chosen
    Probolinggo is a coastal city in East Java, Indonesia, known as a common gateway for tourists visiting the Mount Bromo volcanic area.
  • B. Ponorogo
    Ponorogo is a regency-level town in Indonesia renowned as the cultural heartland of the Reog Ponorogo traditional dance and arts.
  • C. Tulungagung
    Tulungagung is a regency and urban center in southern East Java, Indonesia, known for its marble industry and coastal landscapes along the Indian Ocean.
  • D. Purbalingga
    Purbalingga is a regency and its capital town in Central Java, Indonesia, known for its manufacturing industries and proximity to mountainous tourist areas.
  • E. Nganjuk
    Nganjuk is a regency capital and regional urban center in the province of East Java, Indonesia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245869e188190a196584f36e682da completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17e2f09608190bc8e465e53b39e2e completed April 29, 2026, 3:42 a.m.
Created at: April 17, 2026, 3:35 p.m.