Triple

T5762465
Position Surface form Disambiguated ID Type / Status
Subject Mahameru E127127 entity
Predicate nearbyCity P350 FINISHED
Object Lumajang E147536 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: Lumajang | Statement: [Mahameru, nearbyCity, Lumajang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lumajang
Context triple: [Mahameru, nearbyCity, Lumajang]
  • A. Lumajang Regency chosen
    Lumajang Regency is an administrative region in East Java, Indonesia, known for encompassing part of the area around Mount Semeru, the country’s highest volcano.
  • B. Banyuwangi
    Banyuwangi is a coastal city at the eastern tip of Java, Indonesia, known as a gateway to the Ijen Crater and Bali and for its rich Osing culture.
  • C. Blitar
    Blitar is a city in East Java, Indonesia, best known as the hometown and final resting place of the country’s first president, Sukarno.
  • D. Nganjuk
    Nganjuk is a regency capital and regional urban center in the province of East Java, Indonesia.
  • E. Jember
    Jember is a regency and major urban center in eastern Java, Indonesia, known for its agricultural economy and cultural festivals such as the Jember Fashion Carnaval.
  • 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_69c00833a3fc81908f4bc29ed011b7a6 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0293bbf2081908d40d76c4eb863ae completed March 22, 2026, 5:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3416d3c8190a64d3f4946b84d4b completed March 23, 2026, 6:52 a.m.
Created at: March 22, 2026, 3:49 p.m.