Triple

T4983528
Position Surface form Disambiguated ID Type / Status
Subject Glynis Johns E111945 entity
Predicate notableWork P4 FINISHED
Object Miranda E352329 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: Miranda | Statement: [Glynis Johns, notableWork, Miranda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miranda
Context triple: [Glynis Johns, notableWork, Miranda]
  • A. Miranda
    Miranda is a common Spanish-origin surname shared by numerous notable individuals across the arts, politics, and other fields.
  • B. Miranda
    Miranda is one of Uranus's major moons, known for its unusually varied and geologically complex surface featuring dramatic cliffs and patchwork terrains.
  • C. Miranda chosen
    Miranda is the compassionate and innocent daughter of Prospero in Shakespeare’s play "The Tempest," known for her wonder at the world beyond the island where she has been raised.
  • D. Querença
    Querença is a traditional rural village in Portugal’s Algarve region, known for its whitewashed houses, natural springs, and cultural festivals.
  • E. Karla
    Karla is the elusive Soviet spymaster and primary antagonist of John le Carré’s George Smiley novels, symbolizing the Cold War espionage rivalry between British intelligence and the KGB.
  • 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_69bd441adc208190b70a033a0741d01e completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7255d7b4819098b537df5b1a4c3c completed March 20, 2026, 4:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69be8a13f5448190a49f914d1ba49a7a completed March 21, 2026, 12:07 p.m.
Created at: March 20, 2026, 1:33 p.m.