Triple

T23484302
Position Surface form Disambiguated ID Type / Status
Subject Rodrigo Fernández de Santaella E570489 entity
Predicate workLocation P7 FINISHED
Object Salamanca NE NERFINISHED

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: Salamanca | Statement: [Rodrigo Fernández de Santaella, workLocation, Salamanca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salamanca
Context triple: [Rodrigo Fernández de Santaella, workLocation, Salamanca]
  • A. Salamanca
    Salamanca is a Chilean town and municipality in the Coquimbo Region, known for its agricultural production and location in the Choapa Valley.
  • B. Salamanca chosen
    Salamanca is a historic city in western Spain renowned for its ancient university, golden sandstone architecture, and well-preserved medieval old town.
  • C. Salamanca
    Salamanca is an industrial city in central Mexico known for its major oil refinery and role in the country's petrochemical sector.
  • D. Salamanca
    Salamanca is a small city in western New York State located within the Allegany Reservation of the Seneca Nation, known historically for its railroad and timber industries.
  • E. Alcalá de Henares
    Alcalá de Henares is a historic Spanish city east of Madrid, renowned as the birthplace of Miguel de Cervantes and for its well-preserved university and medieval architecture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b0b01481908f636939bedd804c completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a752c678819087e5c50b8cf87d3d completed April 29, 2026, 6:38 a.m.
Created at: April 17, 2026, 6:03 p.m.