Triple

T16412429
Position Surface form Disambiguated ID Type / Status
Subject Dennis Dugan E398598 entity
Predicate hasWorkedWith P9615 FINISHED
Object Nick Swardson E375229 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: Nick Swardson | Statement: [Dennis Dugan, hasWorkedWith, Nick Swardson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nick Swardson
Context triple: [Dennis Dugan, hasWorkedWith, Nick Swardson]
  • A. Nick Swardson chosen
    Nick Swardson is an American comedian, actor, and writer known for his offbeat characters and frequent collaborations with Adam Sandler in various comedy films and TV shows.
  • B. Ted McGinley
    Ted McGinley is an American actor best known for his roles on television series such as "Married... with Children," "Happy Days," and "The Love Boat."
  • C. Mark Ryan
    Mark Ryan is a British actor and voice artist best known for his work in the Transformers film series and various stage and television roles.
  • D. Denis Leary
    Denis Leary is an American actor and comedian known for his acerbic stand-up style and roles in projects like the TV series "Rescue Me" and the "Ice Age" film franchise.
  • E. David Koechner
    David Koechner is an American character actor and comedian best known for his scene-stealing roles in films like Anchorman and the TV series The Office.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32874a0cc8190874aea10b1d13004 completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ecfd99c8190a4375a0f62aa50d1 completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:09 a.m.