Triple

T18348047
Position Surface form Disambiguated ID Type / Status
Subject Jajaghu E439593 entity
Predicate locatedIn P40 FINISHED
Object Tumpang 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: Tumpang | Statement: [Jajaghu, locatedIn, Tumpang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tumpang
Context triple: [Jajaghu, locatedIn, Tumpang]
  • A. Tumpang chosen
    Tumpang is a subdistrict in Malang Regency, East Java, Indonesia, known for its proximity to historical temples and as a gateway to the Bromo-Tengger-Semeru area.
  • B. Kusno
    Kusno was the birth name of Sukarno, the first President of Indonesia and a leading figure in the country’s independence movement.
  • C. Sampang
    Sampang is a coastal city and regency capital on Madura Island in East Java, Indonesia, known for its traditional Madurese culture and agriculture-based economy.
  • D. Menglembu
    Menglembu is a town in Perak, Malaysia, best known for its production of roasted groundnuts and its location near the city of Ipoh.
  • E. Lumban
    Lumban is a municipality in the Philippine province of Laguna known for its traditional hand-embroidered textiles and scenic lakeside setting along Laguna de Bay.
  • 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_69d8b9175fec8190af865699b4e64d8c completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e514f594f88190a683e6224e091593 completed April 19, 2026, 5:46 p.m.
Created at: April 10, 2026, 10:37 a.m.