Triple
T22637957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clerks II |
E558732
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Jay |
—
|
NE NERFINISHED |
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: Jay | Statement: [Clerks II, featuresCharacter, Jay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jay Context triple: [Clerks II, featuresCharacter, Jay]
-
A.
Jay
Jay is the surname of John Jay, a prominent American Founding Father and the first Chief Justice of the United States.
-
B.
Jay
Jay is a former American football placekicker and current sports commentator best known for his long NFL career and broadcasting work.
-
C.
Jay
chosen
Jay is a foul-mouthed, slacker stoner character from Kevin Smith’s View Askewniverse, best known as one half of the comedic duo Jay and Silent Bob.
-
D.
Jay
Jay is the given name of Whittaker Chambers, the American writer and former Soviet spy best known for his role in the Alger Hiss case.
-
E.
Jay
Jay is the commonly used nickname of Jay Cutler, a former NFL quarterback best known for his tenure with the Chicago Bears.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1700edb608190ad786ff7fafea0da |
completed | April 29, 2026, 2:42 a.m. |
Created at: April 17, 2026, 3:04 p.m.