Triple

T12863360
Position Surface form Disambiguated ID Type / Status
Subject Magdalena Ortega y Mesa E307651 entity
Predicate givenName P17 FINISHED
Object Magdalena E863412 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: Magdalena | Statement: [Magdalena Ortega y Mesa, givenName, Magdalena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magdalena
Context triple: [Magdalena Ortega y Mesa, givenName, Magdalena]
  • A. Magdalena chosen
    Magdalena is one of the central daughters in Federico García Lorca’s tragedy "The House of Bernarda Alba," embodying the repressed desires and frustrations of women living under strict patriarchal control.
  • B. Magdalena
    Magdalena is the given first name of Swedish opera singer and environmental activist Malena Ernman.
  • C. Magdalena
    Magdalena is a historic town in the Mexican state of Jalisco, known for its role in the tequila-producing region and its proximity to agave landscapes and traditional distilleries.
  • D. Erna
    Erna is the given name of Erna Schneider Hoover, an American mathematician and pioneering computer scientist known for revolutionizing telephone switching systems.
  • E. Maritta
    Maritta is a feminine given name, typically considered a variant of names like Marita or Maria used in various European cultures.
  • 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_69d7bdf5e7cc8190be357278bc5ba3bb completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9708cf6b48190886a99e04d85d348 completed April 10, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69bade6ec81908e3123b96837f104 completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:37 p.m.