Triple

T22950993
Position Surface form Disambiguated ID Type / Status
Subject BCE E570013 entity
Predicate headquartersLocation P62 FINISHED
Object Quito NE NERFINISHED

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: [BCE, headquartersLocation, Quito]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quito
Context triple: [BCE, headquartersLocation, 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. Tulcán
    Tulcán is a city in northern Ecuador, capital of Carchi Province, known as a key Andean border crossing with Colombia and for its famous topiary cemetery.
  • E. Bogotá
    Bogotá is the high-altitude capital and largest city of Colombia, known as a major political, economic, and cultural center in South America.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2459199d08190a8184ee2aa935842 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f181a1b334819097a4e9ea8a54209c completed April 29, 2026, 3:57 a.m.
Created at: April 17, 2026, 3:46 p.m.