Triple

T10909492
Position Surface form Disambiguated ID Type / Status
Subject La Virgen de Quito E257656 entity
Predicate locatedIn P40 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: [La Virgen de Quito, locatedIn, Quito]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quito
Context triple: [La Virgen de Quito, locatedIn, 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. Quito–Guayaquil
    Quito–Guayaquil is a major domestic air route in Ecuador connecting the capital city Quito with the coastal city of Guayaquil.
  • D. Bogotá
    Bogotá is the high-altitude capital and largest city of Colombia, known as a major political, economic, and cultural center in South America.
  • E. La Paz
    La Paz is a municipality in the province of Tarlac in the Philippines, known for its agricultural economy and role as a local commercial center.
  • 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_69d6aa8550c8819095508a2ed9acf3db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d77068e5488190bbc881ebf51d6b2e completed April 9, 2026, 9:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23b8b3fd48190b36e34dc19fa5193 completed April 17, 2026, 1:54 p.m.
Created at: April 8, 2026, 9:22 p.m.