Triple

T13908539
Position Surface form Disambiguated ID Type / Status
Subject Province of Cuenca E334423 entity
Predicate hasMunicipality P847 FINISHED
Object Cuenca E339278 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: Cuenca | Statement: [Province of Cuenca, hasMunicipality, Cuenca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cuenca
Context triple: [Province of Cuenca, hasMunicipality, Cuenca]
  • A. Cuenca
    Cuenca is a historic city in southern Ecuador known for its well-preserved colonial architecture and cultural significance.
  • B. Cuenca chosen
    Cuenca is a historic Spanish city renowned for its medieval architecture and dramatic “hanging houses” perched above deep river gorges.
  • C. Cuenca
    Cuenca is a landlocked municipality in the province of Batangas in the Philippines, known for Mount Macolod and its agricultural communities.
  • D. Calarcá
    Calarcá is a Colombian town and municipality in the coffee-growing Quindío Department, known for its cultural heritage and role in the Coffee Cultural Landscape.
  • E. 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.
  • 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_69d81c5eaa9c819083b1ff8689179565 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2721ec6c8190888f4a9d004eb8e0 completed April 14, 2026, 11:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69fba1c26ba08190b19560123691fda4 completed May 6, 2026, 8:17 p.m.
Created at: April 9, 2026, 10:16 p.m.