Triple

T14804682
Position Surface form Disambiguated ID Type / Status
Subject Purity E348000 entity
Predicate setting P1957 FINISHED
Object Bolivia E3661 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: Bolivia | Statement: [Purity, setting, Bolivia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bolivia
Context triple: [Purity, setting, Bolivia]
  • A. Bolivia chosen
    Bolivia is a landlocked country in central South America known for its diverse indigenous cultures, Andean and Amazonian landscapes, and administrative capitals La Paz and Sucre.
  • B. Argentina and Bolivia
    Argentina and Bolivia are neighboring South American countries that share a long Andean and lowland frontier, including sections defined by the Bermejo River.
  • C. Paraguay
    Paraguay is a landlocked country in central South America known for its bilingual Spanish and Guaraní culture and its location along the Paraguay and Paraná rivers.
  • D. Iperu
    Iperu is a prominent town in Ogun State, southwestern Nigeria, known as an important commercial and cultural center of the Remo region.
  • E. Peru
    Peru is a South American country known for its rich Inca heritage, diverse landscapes from Andes mountains to Amazon rainforest, and the iconic archaeological site of Machu Picchu.
  • 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_69d822ea8b7c819097dfadf3d45545e6 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decf32666081908e84f985c47eb963 completed April 14, 2026, 11:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24c6b3008190a0fac1dace40361a completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:34 a.m.