Triple

T5694002
Position Surface form Disambiguated ID Type / Status
Subject David Magee E125491 entity
Predicate basedOnWorkBy P2806 FINISHED
Object Allan Knee E514040 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: Allan Knee | Statement: [David Magee, basedOnWorkBy, Allan Knee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Allan Knee
Context triple: [David Magee, basedOnWorkBy, Allan Knee]
  • A. Allan Knee chosen
    Allan Knee is an American playwright and screenwriter best known for creating the stage play that inspired the film "Finding Neverland."
  • B. Allan Little
    Allan Little is a British journalist and former BBC correspondent known for his in-depth reporting on international conflicts and political affairs.
  • C. Allan Burns
    Allan Burns was an American television writer and producer best known for co-creating influential sitcoms such as The Mary Tyler Moore Show.
  • D. Ken Ralston
    Ken Ralston is an acclaimed visual effects supervisor known for his groundbreaking work on major films such as the Star Wars and Back to the Future series.
  • E. Brian Dutcher
    Brian Dutcher is an American college basketball coach best known for leading the San Diego State Aztecs to national prominence, including a run to the 2023 NCAA championship game.
  • 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_69c0082bb19c8190823a4facd3cba79b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023e7dbe48190850b501f223614e3 completed March 22, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a528a348190a7f6fd4cc3b76c92 completed March 22, 2026, 9:08 p.m.
Created at: March 22, 2026, 3:44 p.m.