Triple

T8541851
Position Surface form Disambiguated ID Type / Status
Subject CONAIE E202215 entity
Predicate headquartersCountry P62 FINISHED
Object Ecuador E1141 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: Ecuador | Statement: [CONAIE, headquartersCountry, Ecuador]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ecuador
Context triple: [CONAIE, headquartersCountry, Ecuador]
  • A. Ecuador chosen
    Ecuador is a South American country on the Pacific coast, known for its diverse geography that includes part of the Amazon rainforest, the Andean highlands, and the Galápagos Islands.
  • B. 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.
  • C. Peru
    Peru is a small rural town in Berkshire County, Massachusetts, known for its elevated terrain and quiet, forested landscape in western New England.
  • D. Colombia
    Colombia is a station on Madrid's Metro network, serving Line 8 and acting as an important interchange point in the city's public transportation system.
  • E. Colombia
    Colombia is a transcontinental country in northern South America, known for its diverse landscapes from Andes mountains to Amazon rainforest, rich cultural heritage, and major cities like Bogotá and Medellín.
  • 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_69ca832461e88190a654c5e44e233aa8 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6e26be48190b10bc62fad178dad completed March 31, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce891a1fac8190bcae4063b24c760a completed April 2, 2026, 3:19 p.m.
Created at: March 30, 2026, 6:18 p.m.