Triple
T16161377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Do-Over |
E392187
|
entity |
| Predicate | castMember |
P1668
|
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: [The Do-Over, castMember, Nick Swardson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nick Swardson Context triple: [The Do-Over, castMember, 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21e5f0cb48190aae995d88382e055 |
completed | April 17, 2026, 11:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000785fcd481909ddf92cf9cc5c0aa |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 5:02 a.m.