Triple

T17446754
Position Surface form Disambiguated ID Type / Status
Subject Banabans E424806 entity
Predicate originalInhabitantsOf P3032 FINISHED
Object Banaba NE NERFINISHED

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: Banaba | Statement: [Banabans, originalInhabitantsOf, Banaba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Banaba
Context triple: [Banabans, originalInhabitantsOf, Banaba]
  • A. Banaba chosen
    Banaba is a raised coral island in the Pacific Ocean that is part of the Republic of Kiribati and is known for its rich phosphate deposits and dramatic environmental history.
  • B. Shikitsu
    Shikitsu is a notable district within Naniwa-ku in Osaka, Japan, known for its urban character and local commercial activity.
  • C. Senna
    Senna is a critically acclaimed 2010 documentary film that chronicles the life, career, and tragic death of legendary Brazilian Formula One driver Ayrton Senna.
  • D. Rajula
    Rajula is a town in Gujarat, India, known for its stone quarries and coastal proximity along the Arabian Sea.
  • E. Tinospora
    Tinospora is a genus of climbing shrubs known for their medicinally used stems and widespread occurrence in tropical and subtropical regions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e44ffc89e4819096372cc55b40cc3b completed April 19, 2026, 3:46 a.m.
Created at: April 10, 2026, 5:47 a.m.