Triple

T3515079
Position Surface form Disambiguated ID Type / Status
Subject Catherine of Aragon E74286 entity
Predicate birthPlace P1 FINISHED
Object Alcalá de Henares E91758 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: Alcalá de Henares | Statement: [Catherine of Aragon, birthPlace, Alcalá de Henares]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alcalá de Henares
Context triple: [Catherine of Aragon, birthPlace, Alcalá de Henares]
  • A. Alcalá de Henares chosen
    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.
  • B. Alcalá la Real
    Alcalá la Real is a historic town in southern Spain known for its imposing La Mota fortress and strategic location between Granada and Jaén.
  • C. Salamanca
    Salamanca is a Chilean town and municipality in the Coquimbo Region, known for its agricultural production and location in the Choapa Valley.
  • D. Salamanca
    Salamanca is a historic city in western Spain renowned for its ancient university, golden sandstone architecture, and well-preserved medieval old town.
  • E. Salamanca
    Salamanca is an industrial city in central Mexico known for its major oil refinery and role in the country's petrochemical sector.
  • 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_69ad85cfb5c881909c9a2edd9d6043cc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc30362c81908ca7497a6a935cc6 completed March 8, 2026, 6:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bb809d288190b4904b292fe9a627 completed March 13, 2026, 7:23 a.m.
Created at: March 8, 2026, 3:19 p.m.