Triple

T5656679
Position Surface form Disambiguated ID Type / Status
Subject Senaru E124636 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: [Senaru, locatedIn, Lombok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lombok
Context triple: [Senaru, locatedIn, Lombok]
  • A. Lombok chosen
    Lombok is an Indonesian island east of Bali, known for its volcanic Mount Rinjani, beaches, and Sasak culture.
  • B. Nambui
    Nambui was a Mongol empress consort of the Yuan dynasty and a prominent wife of Kublai Khan, influential in the imperial court after the death of his first empress.
  • C. Pakurumo
    Pakurumo is a popular Afrobeat song by Nigerian artist Wizkid, known for its upbeat rhythm and dance-friendly vibe.
  • D. Hatta
    Hatta is an Indonesian surname most prominently associated with Mohammad Hatta, the country’s first vice president and a leading figure in the struggle for independence.
  • E. 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.
  • 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_69c0082774a481909d7e63fb2aad56ac completed March 22, 2026, 3:17 p.m.
NER Named-entity recognition batch_69c022fb0b74819084782411bd172834 completed March 22, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d9ec1248190aff680acb4064a49 completed March 22, 2026, 8:14 p.m.
Created at: March 22, 2026, 3:42 p.m.