Triple

T13022331
Position Surface form Disambiguated ID Type / Status
Subject Santa Clara Canton E326206 entity
Predicate locatedInCountry P40 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: [Santa Clara Canton, locatedInCountry, Ecuador]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ecuador
Context triple: [Santa Clara Canton, locatedInCountry, 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. Iperu
    Iperu is a prominent town in Ogun State, southwestern Nigeria, known as an important commercial and cultural center of the Remo region.
  • C. 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.
  • D. Peru
    Peru is a small rural town in Berkshire County, Massachusetts, known for its elevated terrain and quiet, forested landscape in western New England.
  • 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_69d8076cc45c81908123123f43e69266 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97ed05e9c8190a4f208662bca0602 completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c11290e08190a41c162d47094203 completed May 3, 2026, 3:29 a.m.
Created at: April 9, 2026, 8:52 p.m.