Triple

T3378326
Position Surface form Disambiguated ID Type / Status
Subject Spyfall E71118 entity
Predicate featuresAntagonist P32100 FINISHED
Object Daniel Barton E385396 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: Daniel Barton | Statement: [Spyfall, featuresAntagonist, Daniel Barton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Barton
Context triple: [Spyfall, featuresAntagonist, Daniel Barton]
  • A. Daniel Barton chosen
    Daniel Barton is a powerful tech magnate and covert MI6 double agent who serves as a primary antagonist in the Doctor Who episode "Spyfall."
  • B. Daniel Butterfield
    Daniel Butterfield was a Union Army general in the American Civil War, best known for composing the bugle call "Taps."
  • C. Richard Bristow
    Richard Bristow was a 16th-century English Catholic scholar and theologian who contributed to the development and annotation of the Douay–Rheims Bible.
  • D. Barton Bendish
    Barton Bendish is a small rural village and civil parish in Norfolk, England, known for its historic churches and traditional countryside landscape.
  • E. David Bretherton
    David Bretherton was an American film editor known for his work on numerous Hollywood productions, including the musical comedy "The Best Little Whorehouse in Texas."
  • 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_69ad85a7f80c8190a05e43013f298942 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb2eacb5c81908071a1dacc9a897a completed March 8, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503d6cd9c81908acb288091503ec1 completed March 14, 2026, 6:44 a.m.
Created at: March 8, 2026, 3:14 p.m.