Triple

T13716696
Position Surface form Disambiguated ID Type / Status
Subject Two Women E328918 entity
Predicate hasCharacter P2308 FINISHED
Object Vera E328915 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 | Statement: [Two Women, hasCharacter, Vera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vera
Context triple: [Two Women, hasCharacter, 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 chosen
    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.

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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd4398f0448190810c840a82228706 completed April 13, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d5878948190a2aaab2ba31bd1ed completed May 3, 2026, 7:09 p.m.
Created at: April 9, 2026, 9:54 p.m.