Triple

T10942153
Position Surface form Disambiguated ID Type / Status
Subject Beatriz Enríquez de Arana E258498 entity
Predicate associatedPlace P1481 FINISHED
Object Córdoba E524940 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: Córdoba | Statement: [Beatriz Enríquez de Arana, associatedPlace, Córdoba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Córdoba
Context triple: [Beatriz Enríquez de Arana, associatedPlace, Córdoba]
  • A. Córdoba
    Córdoba is a major city in central Argentina known for its industrial base, universities, and strategic military presence.
  • B. Córdoba chosen
    Córdoba is a historic city in southern Spain renowned for its rich Moorish and medieval heritage, including the iconic Mezquita-Catedral.
  • C. Granada
    Granada is a small rural town in southeastern Colorado, historically known as the site of the World War II-era Amache Japanese American internment camp.
  • D. Granada
    Granada is a historic colonial city in western Nicaragua, known for its well-preserved Spanish architecture and location on the shores of Lake Nicaragua.
  • E. Granada
    Granada is a Colombian town and municipality in the Meta Department, known for its agricultural economy and role as a regional service center in the Llanos Orientales.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770c33a7c8190b3347944f68ee431 completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e4830a903481909eaf327457eabf2b completed April 19, 2026, 7:23 a.m.
Created at: April 8, 2026, 9:23 p.m.