Triple

T22698422
Position Surface form Disambiguated ID Type / Status
Subject University of Cuenca E561247 entity
Predicate locatedIn P40 FINISHED
Object Cuenca, Ecuador 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: Cuenca, Ecuador | Statement: [University of Cuenca, locatedIn, Cuenca, Ecuador]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cuenca, Ecuador
Context triple: [University of Cuenca, locatedIn, Cuenca, Ecuador]
  • A. San Miguel, Ecuador
    San Miguel, Ecuador is a small town in the Bolívar Province of central Ecuador, known as a local administrative and commercial center in the Andean highlands.
  • B. Cuenca
    Cuenca is a landlocked municipality in the province of Batangas in the Philippines, known for Mount Macolod and its agricultural communities.
  • C. Cuenca chosen
    Cuenca is a historic city in southern Ecuador known for its well-preserved colonial architecture and cultural significance.
  • D. Cuenca
    Cuenca is a historic Spanish city renowned for its medieval architecture and dramatic “hanging houses” perched above deep river gorges.
  • E. Quevedo, Ecuador
    Quevedo, Ecuador is a mid-sized city in the coastal lowlands of central-western Ecuador, known as an important agricultural and commercial hub in the Los Ríos province.
  • 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_69e2454e615481909c177440be559d2c completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f178a008448190b393335704128fe8 completed April 29, 2026, 3:18 a.m.
Created at: April 17, 2026, 3:14 p.m.