Triple

T11844772
Position Surface form Disambiguated ID Type / Status
Subject Professor Marvel E281745 entity
Predicate screenwritersOfWork P48034 FINISHED
Object Edgar Allan Woolf E48315 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: Edgar Allan Woolf | Statement: [Professor Marvel, screenwritersOfWork, Edgar Allan Woolf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edgar Allan Woolf
Context triple: [Professor Marvel, screenwritersOfWork, Edgar Allan Woolf]
  • A. Edgar Allan Woolf chosen
    Edgar Allan Woolf was an American playwright and screenwriter best known for co-writing the screenplay of the classic 1939 film "The Wizard of Oz."
  • B. John Woolf
    John Woolf was a prominent British film producer known for backing acclaimed mid-20th-century films, including several major literary adaptations and award-winning dramas.
  • C. Edward Wild
    Edward Wild is a cinematographer known for his work on feature films such as the romantic comedy "Chalet Girl."
  • D. Edgar Howard
    Edgar Howard was a U.S. Congressman from Nebraska known for his leadership on Native American policy and as a key legislative advocate of the Indian New Deal era.
  • E. John Bedford Lloyd
    John Bedford Lloyd is an American character actor known for his supporting roles in films and television series, including appearances in major dramas and thrillers.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a65b5ff08190bb58361f6a6acdca completed April 10, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69f1679729c08190a9f6750586f90d8d completed April 29, 2026, 2:06 a.m.
Created at: April 8, 2026, 9:43 p.m.