Triple

T6295931
Position Surface form Disambiguated ID Type / Status
Subject Bromo Tengger Semeru National Park E141130 entity
Predicate nearestCity P350 FINISHED
Object Probolinggo E135336 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: Probolinggo | Statement: [Bromo Tengger Semeru National Park, nearestCity, Probolinggo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Probolinggo
Context triple: [Bromo Tengger Semeru National Park, nearestCity, 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. Nganjuk
    Nganjuk is a regency capital and regional urban center in the province of East Java, Indonesia.
  • E. Jombang
    Jombang is a regency-level town in Indonesia known as an important regional center in the province of East Java.
  • 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_69c008cdf2ac8190bb640c94478fb4ed completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0643ac2b48190b2db036ce709e7ea completed March 22, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62d25ff1081908d07c649555f17c4 completed March 27, 2026, 7:09 a.m.
Created at: March 22, 2026, 4:27 p.m.