Triple

T1053797
Position Surface form Disambiguated ID Type / Status
Subject Mount Rinjani E22756 entity
Predicate locatedIn P40 FINISHED
Object Lombok E20548 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: Lombok | Statement: [Mount Rinjani, locatedIn, Lombok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lombok
Context triple: [Mount Rinjani, locatedIn, Lombok]
  • A. Lombok chosen
    Lombok is an Indonesian island east of Bali, known for its volcanic Mount Rinjani, beaches, and Sasak culture.
  • B. Yanam
    Yanam is a coastal town and district enclave of the Union Territory of Puducherry in India, historically influenced by French colonial rule and culturally linked to the Telugu-speaking region of Andhra Pradesh.
  • C. Lapa
    Lapa is a historic and bohemian neighborhood in Rio de Janeiro, Brazil, famous for its vibrant nightlife, samba clubs, and iconic aqueduct arches.
  • D. Madura
    Madura is an island off the northeastern coast of Java in Indonesia, known for its distinct Madurese culture and traditional bull races.
  • E. Shiga
    Shiga is a landlocked prefecture in central Japan known for encompassing Lake Biwa, the country’s largest freshwater lake, and for its historical sites and natural scenery.
  • 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_69ac4c1b4c3481909ec58291dc9cc32f completed March 7, 2026, 4:02 p.m.
Created at: March 1, 2026, 7:42 p.m.