Triple

T7707399
Position Surface form Disambiguated ID Type / Status
Subject Elo River E174653 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Magelang E125545 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: Magelang | Statement: [Elo River, hasNearbySettlement, Magelang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magelang
Context triple: [Elo River, hasNearbySettlement, Magelang]
  • A. Magelang chosen
    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.
  • B. Salatiga
    Salatiga is a small city in Central Java, Indonesia, known for its cool climate, educational institutions, and location between Mount Merbabu and Mount Telomoyo.
  • C. Magelang Regency
    Magelang Regency is an administrative region in Central Java, Indonesia, known for its proximity to the Borobudur Temple and its mountainous landscapes surrounding the city of Magelang.
  • D. Purworejo
    Purworejo is a regency in Central Java, Indonesia, known for its agricultural landscape and proximity to the southern coast of Java.
  • E. Magetan
    Magetan is a regency and town in East Java, Indonesia, known for its cool climate, agricultural production, and proximity to the scenic Sarangan Lake and Mount Lawu.
  • 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_69c6995b3e8c8190833108f883d5f53c completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c702a93f288190a53bbe6620417528 completed March 27, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be2583508190bda9a88e149fe264 completed March 29, 2026, 5:52 a.m.
Created at: March 27, 2026, 4:04 p.m.