Triple

T6785471
Position Surface form Disambiguated ID Type / Status
Subject Ngawi E155790 entity
Predicate distanceTo P350 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: [Ngawi, distanceTo, Madiun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madiun
Context triple: [Ngawi, distanceTo, 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. 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.
  • D. Kediri
    Kediri is a historic city in Indonesia known for its role as a former Javanese kingdom center and as an important economic hub in modern East Java.
  • E. Malang
    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.
  • 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_69c6881770fc8190972b2906390380f5 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d28de0348190998751fd546bfd02 completed March 27, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ad6644f4819080db0a3981470d96 completed March 28, 2026, 10:28 a.m.
Created at: March 27, 2026, 2:14 p.m.