Triple

T199488
Position Surface form Disambiguated ID Type / Status
Subject President of Ecuador E4069 entity
Predicate seat P75 FINISHED
Object Quito E8614 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: Quito | Statement: [President of Ecuador, seat, Quito]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quito
Context triple: [President of Ecuador, seat, Quito]
  • A. Quito chosen
    Quito is the high-altitude Andean city that serves as Ecuador’s political and cultural center, renowned for its well-preserved colonial historic center and dramatic mountain setting.
  • B. Guayaquil
    Guayaquil is a major Pacific port city in southwestern Ecuador and the country’s principal commercial and industrial center.
  • C. Bogotá
    Bogotá is the high-altitude capital and largest city of Colombia, known as a major political, economic, and cultural center in South America.
  • D. La Paz
    La Paz is the administrative capital and one of the major cities of Bolivia, known for its dramatic setting in a deep valley of the Andes at one of the highest elevations of any capital city in the world.
  • E. Sucre
    Sucre is the constitutional capital of Bolivia, known for its well-preserved colonial architecture and historical significance in the country’s independence.
  • 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_69a254bca59881909a15e1496f1508c7 completed Feb. 28, 2026, 2:36 a.m.
NER Named-entity recognition batch_69a25bcc6dc88190b8c24b485588dfe4 completed Feb. 28, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69a39d0168508190b6f6766a75dd0e34 completed March 1, 2026, 1:57 a.m.
Created at: Feb. 28, 2026, 2:44 a.m.