Triple

T22146023
Position Surface form Disambiguated ID Type / Status
Subject Grace Margaret Mulligan E547289 entity
Predicate hasDialogueWith P12142 FINISHED
Object Vera NE NERFINISHED

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: Vera | Statement: [Grace Margaret Mulligan, hasDialogueWith, Vera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vera
Context triple: [Grace Margaret Mulligan, hasDialogueWith, Vera]
  • A. Vera
    Vera Rubin was an influential American astronomer whose pioneering work on galaxy rotation curves provided key evidence for the existence of dark matter.
  • B. Vera
    Vera is a feminine given name of Slavic origin, commonly used in Russian and other Eastern European cultures, meaning "faith."
  • C. Vera
    Vera is a memorable supporting character from the 1989 Eddie Murphy film "Harlem Nights," known for her tough, comedic persona.
  • D. Vera
    Vera is a historic coastal town and municipality in Spain’s Andalusian province of Almería, known for its beaches and traditional whitewashed architecture.
  • E. Vera
    "Vera" is a British crime drama television series, based on Ann Cleeves' novels, that follows the sharp but irascible Detective Chief Inspector Vera Stanhope as she solves complex murder cases in North East England.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

Provenance (2 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_69e11e3a95d88190a3bd80d9471976c3 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129f097248190a8a3cdff1593b5b5 completed April 28, 2026, 9:43 p.m.
Created at: April 16, 2026, 8:33 p.m.