Triple

T20792192
Position Surface form Disambiguated ID Type / Status
Subject Mount Sumbing E511804 entity
Predicate nearbyCity P350 FINISHED
Object Temanggung 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: Temanggung | Statement: [Mount Sumbing, nearbyCity, Temanggung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Temanggung
Context triple: [Mount Sumbing, nearbyCity, Temanggung]
  • A. Temanggung chosen
    Temanggung is a regency in Central Java, Indonesia, known for its tobacco plantations and mountainous landscape near Mount Sindoro and Mount Sumbing.
  • B. Wonosobo
    Wonosobo is a highland town in Central Java, Indonesia, known as a gateway to the Dieng Plateau and its scenic volcanic landscapes.
  • C. Trenggalek
    Trenggalek is a regency and its capital town in southern East Java, Indonesia, known for its coastal landscapes, caves, and agricultural economy.
  • D. Kebumen
    Kebumen is a regency-level town in southern Central Java, Indonesia, known for its agricultural surroundings, coastal areas, and proximity to karst landscapes and caves.
  • E. Banjarnegara
    Banjarnegara is a regency-level town in Central Java, Indonesia, known as an administrative and economic center in the region.
  • 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_69e0b4cb83948190bd57bec21d78ed53 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2910d488190bc4be37512effc86 completed April 21, 2026, 12:19 a.m.
Created at: April 16, 2026, 12:38 p.m.