Triple

T6997032
Position Surface form Disambiguated ID Type / Status
Subject Magda Goebbels E162241 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: [Magda Goebbels, givenName, Magdalena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magdalena
Context triple: [Magda Goebbels, givenName, Magdalena]
  • A. Magdalena chosen
    Magdalena is the given first name of Swedish opera singer and environmental activist Malena Ernman.
  • B. Erna
    Erna is the given name of Erna Schneider Hoover, an American mathematician and pioneering computer scientist known for revolutionizing telephone switching systems.
  • C. Maritta
    Maritta is a feminine given name, typically considered a variant of names like Marita or Maria used in various European cultures.
  • D. Mialet
    Mialet is a commune in the Gard department of southern France, known for its scenic Cévennes landscape and proximity to notable caves and natural attractions.
  • E. Bassein
    Bassein is a historic coastal town in western India, now known as Vasai, notable for its strategic port and colonial-era fortifications that played a key role in regional power struggles.
  • 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_69c68857ffc08190857dc62cd5253777 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dbedafa48190af0d2b47e3a1e17e completed March 27, 2026, 7:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a2465908190b69454f6215365b0 completed March 28, 2026, 5:41 a.m.
Created at: March 27, 2026, 2:32 p.m.