Triple

T19220948
Position Surface form Disambiguated ID Type / Status
Subject São Gabriel da Cachoeira E480610 entity
Predicate hasOfficialLanguage P236 FINISHED
Object Baniwa 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: Baniwa | Statement: [São Gabriel da Cachoeira, hasOfficialLanguage, Baniwa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baniwa
Context triple: [São Gabriel da Cachoeira, hasOfficialLanguage, Baniwa]
  • A. Baniata
    Baniata is an Oceanic language of the Meso-Melanesian group spoken in the Solomon Islands.
  • B. Bani
    Bani was a daughter of the prominent Indian freedom fighter and lawyer Chittaranjan (C. R.) Das.
  • C. Bani
    Bani is a coastal municipality in the province of Pangasinan in the Philippines, known for its beaches, agricultural produce, and scenic rural landscapes.
  • D. Bantumi
    Bantumi is a digital version of the traditional Mancala-style board game that was popularized on early Nokia mobile phones.
  • E. Kurripako-Baniwa chosen
    Kurripako-Baniwa is an Arawakan language spoken by Indigenous communities in the Upper Rio Negro region of Brazil, Colombia, and Venezuela.
  • 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_69d8e8cb8c348190b52075823911c869 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fa3e8d488190a93fb743dabd0ffb completed April 20, 2026, 10:04 a.m.
Created at: April 10, 2026, 1:24 p.m.