Triple

T7767660
Position Surface form Disambiguated ID Type / Status
Subject Baniwa language E178989 entity
Predicate hasDialect P4251 FINISHED
Object Curripaco E643936 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: Curripaco | Statement: [Baniwa language, hasDialect, Curripaco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Curripaco
Context triple: [Baniwa language, hasDialect, Curripaco]
  • A. Curripaco chosen
    Curripaco is an indigenous Arawakan language spoken by the Curripaco people in the Amazon region of Brazil, Colombia, and Venezuela.
  • B. Guabiraba
    Guabiraba is a neighborhood and administrative district located in the northern part of Recife, in the state of Pernambuco, Brazil.
  • C. Horcón
    Horcón is a small rural village in Chile’s Elqui Valley, known for its scenic Andean surroundings and traditional agricultural lifestyle.
  • D. Urubu-Kaapor
    Urubu-Kaapor is an indigenous language of the Tupi–Guaraní family spoken by the Ka'apor people in the Amazon region of Brazil.
  • E. Nasuella
    Nasuella is a small genus of South American carnivorous mammals known as mountain coatis, characterized by their elongated snouts and arboreal habits.
  • 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_69c69f30602c819082ab52cd4af5c592 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c70435b7f88190a5e68e6ae701c58f completed March 27, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7e4976c81909ff34dcdcae96999 completed March 29, 2026, 6:34 a.m.
Created at: March 27, 2026, 4:11 p.m.