Triple
T17495544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Avery |
E426047
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | License to Drive |
—
|
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: License to Drive | Statement: [James Avery, appearedIn, License to Drive]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: License to Drive Context triple: [James Avery, appearedIn, License to Drive]
-
A.
License to Drive
chosen
License to Drive is a 1988 teen comedy film about a teenager who secretly takes his grandfather’s prized Cadillac out for a wild night after failing his driving test.
-
B.
Licensed to Drive
"Licensed to Drive" is a song by the American rock band Black Mountain.
-
C.
Licensed to Drive (Edit)
"Licensed to Drive (Edit)" is a shortened, radio-friendly version of Black Mountain's song "Licensed to Drive."
-
D.
The Drive
The Drive is a vibrant, culturally diverse neighborhood and commercial district in East Vancouver known for its eclectic shops, restaurants, and arts scene.
-
E.
The Driver's Seat
The Driver's Seat is a darkly comic, psychologically intense novella by Muriel Spark that follows a disturbed woman’s self-destructive journey toward a preordained violent end.
- 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4520dd9508190872a71d3722228e2 |
completed | April 19, 2026, 3:54 a.m. |
Created at: April 10, 2026, 5:48 a.m.