Triple

T15549082
Position Surface form Disambiguated ID Type / Status
Subject Madiun Regency E370692 entity
Predicate hasFormerCapital P3417 FINISHED
Object Madiun E182493 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: Madiun | Statement: [Madiun Regency, hasFormerCapital, Madiun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madiun
Context triple: [Madiun Regency, hasFormerCapital, Madiun]
  • A. Madiun chosen
    Madiun is a city in eastern Java, Indonesia, known as a regional economic and transportation hub with a strong railway and agricultural industry presence.
  • B. Pasuruan
    Pasuruan is a city in East Java, Indonesia, known as a gateway to the popular Mount Bromo volcanic tourism area.
  • C. Citeureup
    Citeureup is a district in West Java, Indonesia, known as one of the industrial and residential areas within the Bogor metropolitan region.
  • D. Tuban
    Tuban is a major city in Yemen’s Lahij Governorate, serving as an important local center for administration and commerce.
  • E. Tuban
    Tuban is a coastal town and regency capital in northern East Java, Indonesia, known historically as a trading port and for its cultural and religious heritage sites.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a93121881909d88ca55a39252ac completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff455dfbcc8190a93e90c59b2d3045 completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 4:08 a.m.