Triple
T6954905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pain & Gain |
E161216
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Tony Shalhoub |
E76498
|
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: Tony Shalhoub | Statement: [Pain & Gain, hasCastMember, Tony Shalhoub]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tony Shalhoub Context triple: [Pain & Gain, hasCastMember, Tony Shalhoub]
-
A.
Tony Shalhoub
chosen
Tony Shalhoub is an American actor best known for his Emmy-winning portrayal of the obsessive-compulsive detective Adrian Monk in the television series "Monk."
-
B.
Michael Shalhoub
Michael Shalhoub is an American actor and the brother of Emmy-winning performer Tony Shalhoub.
-
C.
Kelsey Grammer
Kelsey Grammer is an American actor best known for his long-running, Emmy-winning portrayal of Dr. Frasier Crane on the sitcoms "Cheers" and "Frasier."
-
D.
Paul Reiser
Paul Reiser is an American actor, comedian, and writer best known for co-creating and starring in the 1990s sitcom "Mad About You" and for roles in films such as "Aliens" and "Diner."
-
E.
Andre Braugher
Andre Braugher is an American actor acclaimed for his powerful dramatic roles and his Emmy-winning performances in both television and film.
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dace1a94819095311e4288f01784 |
completed | March 27, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7618afb0c8190b1545328c1cee5de |
completed | March 28, 2026, 5:05 a.m. |
Created at: March 27, 2026, 2:29 p.m.