Triple

T1019213
Position Surface form Disambiguated ID Type / Status
Subject Mount Merapi E22001 entity
Predicate nearbyCity P350 FINISHED
Object Klaten E119358 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: Klaten | Statement: [Mount Merapi, nearbyCity, Klaten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Klaten
Context triple: [Mount Merapi, nearbyCity, Klaten]
  • A. Pekalongan
    Pekalongan is an Indonesian coastal city on the island of Java renowned as a major center of batik production and textile arts.
  • B. Magelang
    Magelang is a city in Central Java, Indonesia, known as the gateway to the famous Borobudur Temple and for its surrounding volcanic and rural landscapes.
  • C. Cirebon
    Cirebon is a coastal city in West Java, Indonesia, known as a cultural crossroads blending Sundanese and Javanese influences and serving as a significant regional trading and urban center.
  • D. Boyolali chosen
    Boyolali is a regency in Central Java, Indonesia, known for its agricultural landscape, dairy production, and proximity to several volcanoes including Mount Merapi.
  • E. Tabanan Regency
    Tabanan Regency is an agricultural and coastal region in western Bali, Indonesia, known for its lush rice terraces and the iconic Tanah Lot sea temple.
  • 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_69a493d6e380819097b384986ffc315c completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7dbcf7c8190858b2d16a27bd2ff completed March 1, 2026, 10:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac59978cb4819098118b6348b8a55a completed March 7, 2026, 5 p.m.
Created at: March 1, 2026, 7:41 p.m.