Triple

T1053840
Position Surface form Disambiguated ID Type / Status
Subject Mount Rinjani E22756 entity
Predicate hasNearbyTown P3883 FINISHED
Object Sembalun Lawang E121878 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: Sembalun Lawang | Statement: [Mount Rinjani, hasNearbyTown, Sembalun Lawang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sembalun Lawang
Context triple: [Mount Rinjani, hasNearbyTown, Sembalun Lawang]
  • A. Tangkuban Perahu
    Tangkuban Perahu is a popular stratovolcano in West Java, Indonesia, known for its distinctive boat-like shape and easily accessible craters.
  • B. Sembalun chosen
    Sembalun is a village in East Lombok, Indonesia, known as a primary gateway and starting point for treks up Mount Rinjani.
  • C. Ranggawuni
    Ranggawuni was a 13th-century Javanese king of the Singhasari Kingdom, known for consolidating royal power and laying groundwork for the rise of later Javanese empires.
  • D. Mount Semeru
    Mount Semeru is the highest and one of the most active volcanoes on the Indonesian island of Java, renowned for its frequent eruptions and prominent conical peak.
  • E. Kuta Lombok
    Kuta Lombok is a coastal town on the Indonesian island of Lombok known for its scenic white-sand beaches, surf breaks, and laid-back tourism atmosphere.
  • 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8d669448190955507e2e4975b9f completed March 1, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac429f0580819082d5a2cc6129cb1e completed March 7, 2026, 3:22 p.m.
Created at: March 1, 2026, 7:42 p.m.