Triple

T23305966
Position Surface form Disambiguated ID Type / Status
Subject Qom E590435 entity
Predicate nativeTo P410 FINISHED
Object Gran Chaco 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: Gran Chaco | Statement: [Qom, nativeTo, Gran Chaco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gran Chaco
Context triple: [Qom, nativeTo, Gran Chaco]
  • A. Gran Chaco chosen
    The Gran Chaco is a vast, sparsely populated lowland plain in central South America, known for its hot, semi-arid climate and dry forests spanning parts of Argentina, Paraguay, Bolivia, and Brazil.
  • B. Misiones rainforest
    The Misiones rainforest is a subtropical forest in northeastern Argentina renowned for its rich biodiversity, red-soil landscapes, and iconic Iguazú Falls.
  • C. Pampas
    The Pampas is a vast fertile lowland plain in South America, primarily in Argentina, known for its grasslands, agriculture, and cattle ranching.
  • D. Pampas
    Pampas is a town in central Peru that serves as the administrative and commercial hub of Tayacaja Province in the Huancavelica Region.
  • E. Pampa
    Pampa is a jet trainer aircraft used by the Argentine Air Force, known for its role in pilot training and light attack missions.
  • 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_69e25d1c0ecc8190a355aa229f06d0e0 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1972737c08190bd011776564c3861 completed April 29, 2026, 5:29 a.m.
Created at: April 17, 2026, 5:05 p.m.