Triple
T14102564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friday (film) |
E339419
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Smokey |
E548382
|
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: Smokey | Statement: [Friday (film), character, Smokey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smokey Context triple: [Friday (film), character, Smokey]
-
A.
Smokey
Smokey is a character mentioned in the lyrics of the jazz song "Minnie the Moocher," often associated with the song’s colorful, narrative world of nightlife and mischief.
-
B.
Smokey
Smokey is the bluetick coonhound dog who serves as the live mascot for the University of Tennessee Volunteers athletic teams.
-
C.
Smokey
Smokey is the widely known nickname of legendary American singer, songwriter, and record producer Smokey Robinson.
-
D.
Smokey
chosen
Smokey is the wisecracking, weed-smoking best friend in the 1995 comedy film "Friday," portrayed by Chris Tucker.
-
E.
Smokey
Smokey is an experienced, older race car and former crew chief who mentors Lightning McQueen in the animated film "Cars 3."
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fbbf0b08190ba1ea3657d6db005 |
completed | April 14, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd0b2ade08190a56e9ecf659f83b9 |
completed | May 7, 2026, 5:49 p.m. |
Created at: April 9, 2026, 10:22 p.m.