Triple

T21321622
Position Surface form Disambiguated ID Type / Status
Subject Dan Rowan E525631 entity
Predicate name P16 FINISHED
Object Dan Rowan NE NERFINISHED

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: Dan Rowan | Statement: [Dan Rowan, name, Dan Rowan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Rowan
Context triple: [Dan Rowan, name, Dan Rowan]
  • A. Dan Rowan chosen
    Dan Rowan was an American comedian and television host best known as one half of the comedy duo Rowan & Martin, which fronted the groundbreaking sketch series "Rowan & Martin's Laugh-In."
  • B. Alan Rowe
    Alan Rowe was a British character actor known for his numerous television roles, including multiple appearances in classic science fiction series such as Doctor Who.
  • C. Martin Boddey
    Martin Boddey was a British character actor known for his frequent supporting roles in mid-20th-century films and television, often portraying authority figures such as policemen and officials.
  • 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. Jack Alcott
    Jack Alcott is an American actor best known for playing Harrison Morgan in the television series "Dexter: New Blood."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51ad810819098c12392c8e55f6c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e77ed2640c8190a81b087e2c49c500 completed April 21, 2026, 1:42 p.m.
Created at: April 16, 2026, 4:39 p.m.