Triple

T12395094
Position Surface form Disambiguated ID Type / Status
Subject Region of Ica E296096 entity
Predicate hasCapital P204 FINISHED
Object Ica E284236 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: Ica | Statement: [Region of Ica, hasCapital, Ica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ica
Context triple: [Region of Ica, hasCapital, Ica]
  • A. Ica chosen
    Ica is a city in southern Peru known for its desert landscape, nearby Huacachina oasis, and production of pisco and wine.
  • B. Ica River
    The Ica River is a coastal river in southern Peru that flows through the arid Ica Region, providing vital water resources for agriculture and local communities in an otherwise desert environment.
  • C. Sullana
    Sullana is a city in northwestern Peru known for its agricultural production and location along the Chira River in the Piura region.
  • D. Sangolquí
    Sangolquí is a city in central Ecuador known as a growing suburban and commercial center near the capital, Quito, within Pichincha Province.
  • E. Martos
    Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fd33f048190b205fd21dc513f6a completed April 10, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6347e27b4819085494babfe180488 completed May 2, 2026, 5:29 p.m.
Created at: April 8, 2026, 9:54 p.m.