Triple

T11943507
Position Surface form Disambiguated ID Type / Status
Subject Huacachina E284236 entity
Predicate locatedIn P40 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: [Huacachina, locatedIn, Ica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ica
Context triple: [Huacachina, locatedIn, 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. Sangolquí
    Sangolquí is a city in central Ecuador known as a growing suburban and commercial center near the capital, Quito, within Pichincha Province.
  • C. 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.
  • D. Girón
    Girón is a historic colonial-era town and municipality in northeastern Colombia, renowned for its preserved whitewashed architecture and cobblestone streets.
  • E. Girón
    Girón is a small town in southern Ecuador known for its colonial architecture, Andean landscapes, and historical significance within Azuay Province.
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9034444488190925a6fa6c856ed08 completed April 10, 2026, 2:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69f440a5a9c8819086a94ad60c6881b8 completed May 1, 2026, 5:56 a.m.
Created at: April 8, 2026, 9:45 p.m.