Triple

T11986839
Position Surface form Disambiguated ID Type / Status
Subject Malena Ernman Thunberg E285300 entity
Predicate givenName P17 FINISHED
Object Magdalena E38830 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: [Malena Ernman Thunberg, givenName, Magdalena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magdalena
Context triple: [Malena Ernman Thunberg, givenName, Magdalena]
  • A. 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.
  • B. Magdalena
    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.
  • C. Magdalena chosen
    Magdalena is the given first name of Swedish opera singer and environmental activist Malena Ernman.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903ae28708190a826bad1624343eb completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f47237c23081909044388ff5dc73b3 completed May 1, 2026, 9:28 a.m.
Created at: April 8, 2026, 9:46 p.m.