Triple

T2462850
Position Surface form Disambiguated ID Type / Status
Subject Reserva de Producción de Fauna Chimborazo E54571 entity
Predicate nearbyCity P350 FINISHED
Object Ambato E241446 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: Ambato | Statement: [Reserva de Producción de Fauna Chimborazo, nearbyCity, Ambato]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ambato
Context triple: [Reserva de Producción de Fauna Chimborazo, nearbyCity, Ambato]
  • A. Ambato chosen
    Ambato is a major city in the central Andean region of Ecuador, known for its agricultural production, textile industry, and annual Festival of Fruits and Flowers.
  • B. Antananarivo
    Antananarivo is the capital and largest city of Madagascar, serving as its political, economic, and cultural center.
  • C. Mamoudzou
    Mamoudzou is the largest city and main administrative and economic center of the French overseas department of Mayotte in the Indian Ocean.
  • D. Mpanda
    Mpanda is a town in western Tanzania that serves as an important administrative and commercial hub for the surrounding region.
  • E. Lambaréné
    Lambaréné is a town in western Gabon best known for its location on the Ogooué River and for hosting the historic Albert Schweitzer Hospital.
  • 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_69ab49dee84c819096b50a0049c347ac completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd11f093c8190877db3026d430bd5 completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0d561a081909310113658b98f12 completed March 9, 2026, 4:09 p.m.
Created at: March 6, 2026, 9:44 p.m.