Triple
T14879304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Craig T. Nelson as Hayden Fox |
E349954
|
entity |
| Predicate | notableRelationship |
P1481
|
FINISHED |
| Object | Luther Van Dam |
E349949
|
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: Luther Van Dam | Statement: [Craig T. Nelson as Hayden Fox, notableRelationship, Luther Van Dam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luther Van Dam Context triple: [Craig T. Nelson as Hayden Fox, notableRelationship, Luther Van Dam]
-
A.
Luther Van Dam
chosen
Luther Van Dam is a bumbling yet lovable assistant football coach on the sitcom "Coach," known for his comedic antics and loyalty to head coach Hayden Fox.
-
B.
Rob Van Dam
Rob Van Dam is an American professional wrestler and former WWE and ECW star known for his high-flying style and innovative offensive moves.
-
C.
Brent Goldberg
Brent Goldberg is a screenwriter best known for co-writing the college comedy film "Van Wilder."
-
D.
Nico van Dam
Nico van Dam is a person notable enough to be recognized as a bearer of the Dutch surname "van Dam."
-
E.
John Briscoe
John Briscoe was a renowned engineer and water resources expert recognized globally for his contributions to water management and policy.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e622388190b2bf91cd10b9821d |
completed | April 15, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b5670108190b41ef95dc318be60 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 10, 2026, 1:55 a.m.