Triple

T16780731
Position Surface form Disambiguated ID Type / Status
Subject Wonder Woman film series E407850 entity
Predicate mainCharacter P1183 FINISHED
Object Diana Prince E199708 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: Diana Prince | Statement: [Wonder Woman film series, mainCharacter, Diana Prince]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diana Prince
Context triple: [Wonder Woman film series, mainCharacter, Diana Prince]
  • A. Diana Prince chosen
    Diana Prince is the Amazonian warrior princess better known as Wonder Woman, a DC Comics superhero who leaves her hidden island to protect humanity.
  • B. Melissa Dyne
    Melissa Dyne is an American artist and musician best known as a member of the experimental pop duo The Blow, where she contributes to the group’s sound design and conceptual production.
  • C. Jo Grant
    Jo Grant is a spirited and resourceful companion of the Third Doctor in the classic British science fiction series Doctor Who.
  • D. Jennifer Walters
    Jennifer Walters is a Marvel Comics lawyer who becomes the superhero She-Hulk after receiving a blood transfusion from her cousin Bruce Banner.
  • E. Kate Kane
    Kate Kane is the DC Comics superheroine who becomes Batwoman, a vigilante crime-fighter in Gotham City and cousin to Bruce Wayne.
  • 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_69d8839270588190886720d9519bbf8f completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b214cebc81909de80e74b4bac5f8 completed April 18, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00ab0300e48190ad088cd11098ca34 completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 5:22 a.m.