Triple

T2638217
Position Surface form Disambiguated ID Type / Status
Subject Ica Region E62797 entity
Predicate hasCity P316 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: [Ica Region, hasCity, Ica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ica
Context triple: [Ica Region, hasCity, 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. Girón
    Girón is a historic colonial-era town and municipality in northeastern Colombia, renowned for its preserved whitewashed architecture and cobblestone streets.
  • D. Supía
    Supía is a municipality in the Caldas Department of Colombia, known historically for gold mining and its indigenous Emberá Chamí heritage.
  • E. Balvanera
    Balvanera is a densely populated, traditionally working- and middle-class neighborhood in central Buenos Aires, Argentina, known for its historic architecture, commercial activity, and strong cultural life.
  • 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_69ab4c3f2dcc819082df80f5e032f690 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abd8e470ac8190bd0d6de6805afcd0 completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa04f0d448190adf113831fb5bc42 completed March 10, 2026, 4:38 a.m.
Created at: March 6, 2026, 9:53 p.m.