Triple

T11943543
Position Surface form Disambiguated ID Type / Status
Subject Huacachina oasis E284237 entity
Predicate locatedNear P294 FINISHED
Object city of 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: city of Ica | Statement: [Huacachina oasis, locatedNear, city of Ica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Ica
Context triple: [Huacachina oasis, locatedNear, city of 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. Ciudad Darío
    Ciudad Darío is a Nicaraguan town best known as the birthplace of the influential modernist poet Rubén Darío.
  • C. City of Calasparra
    The City of Calasparra is a historic Spanish town renowned for its rice cultivation and scenic setting in the northwestern part of the Region of Murcia.
  • D. city of La Serena
    The city of La Serena is a historic coastal city in northern Chile known for its colonial architecture, beaches, and role as a regional economic and cultural center.
  • E. Óbidos
    Óbidos is a historic Portuguese town famed for its well-preserved medieval walls, whitewashed houses, and hilltop 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_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.