Triple

T1101354
Position Surface form Disambiguated ID Type / Status
Subject Mount Semeru E24386 entity
Predicate locatedNear P294 FINISHED
Object Malang E28882 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: Malang | Statement: [Mount Semeru, locatedNear, Malang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malang
Context triple: [Mount Semeru, locatedNear, Malang]
  • A. Malang chosen
    Malang is a major city in East Java, Indonesia, known for its cool climate, colonial-era architecture, and proximity to popular mountain and volcanic tourist destinations.
  • B. Surabaya
    Surabaya is Indonesia’s second-largest city and a key commercial and industrial hub on the island of Java, historically serving as one of the region’s most important seaports.
  • C. Pasuruan
    Pasuruan is a city in East Java, Indonesia, known as a gateway to the popular Mount Bromo volcanic tourism area.
  • D. Surakarta
    Surakarta is a historic Javanese city in Central Java, Indonesia, renowned as a traditional cultural center and royal court city closely associated with classical arts such as gamelan music and dance.
  • E. Yogyakarta
    Yogyakarta is a major cultural and educational city on the Indonesian island of Java, renowned for its traditional arts, universities, and proximity to the Borobudur and Prambanan temples.
  • 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_69a4940542308190ac2a0b1f730b7cfc completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b9c079f48190a0e0ddda182f7a01 completed March 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac9971114c81909769b3ad78b95189 completed March 7, 2026, 9:32 p.m.
Created at: March 1, 2026, 7:43 p.m.