Triple

T14527226
Position Surface form Disambiguated ID Type / Status
Subject Barbara Jo Allen E340809 entity
Predicate notableCharacter P1481 FINISHED
Object Vera Vague E985862 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: Vera Vague | Statement: [Barbara Jo Allen, notableCharacter, Vera Vague]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vera Vague
Context triple: [Barbara Jo Allen, notableCharacter, Vera Vague]
  • A. Vera Vague chosen
    Vera Vague was the comedic stage persona of American actress and radio performer Barbara Jo Allen, known for her dizzy, scatterbrained character in films, radio, and early television.
  • B. Vera
    Vera is a historic coastal town and municipality in Spain’s Andalusian province of Almería, known for its beaches and traditional whitewashed architecture.
  • C. Vera
    Vera Rubin was an influential American astronomer whose pioneering work on galaxy rotation curves provided key evidence for the existence of dark matter.
  • D. Vera
    Vera is a memorable supporting character from the 1989 Eddie Murphy film "Harlem Nights," known for her tough, comedic persona.
  • E. Vera
    Vera is a feminine given name of Slavic origin, commonly used in Russian and other Eastern European cultures, meaning "faith."
  • 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_69d822dac79c8190a84a073f3cbaced5 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dea050781881909ed685d94479bf99 completed April 14, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94acd8288190a91bf09220126e13 completed May 8, 2026, 7:45 a.m.
Created at: April 10, 2026, 1:22 a.m.