Triple
T18114869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cruisin' |
E433578
|
entity |
| Predicate | album |
P1995
|
FINISHED |
| Object | Where There's Smoke... |
—
|
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: Where There's Smoke... | Statement: [Cruisin', album, Where There's Smoke...]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Where There's Smoke... Context triple: [Cruisin', album, Where There's Smoke...]
-
A.
Where There's Smoke...
chosen
"Where There's Smoke..." is a 1998 studio album by American singer-songwriter and producer Smokey Robinson.
-
B.
No Smoke
"No Smoke" is a track from The Game's 2019 studio album "Born 2 Rap," showcasing his West Coast hip-hop style and lyrical storytelling.
-
C.
“Smoke”
“Smoke” is a short story by William Faulkner featuring the shrewd small-town lawyer Gavin Stevens as he unravels a mysterious crime.
-
D.
“Smoke”
“Smoke” is a short story by Ivan Turgenev that explores themes of love, disillusionment, and the clash between old and new Russian society.
-
E.
All the Smoke
All the Smoke is a basketball-focused podcast and talk show known for candid, in-depth conversations with NBA players and other sports and entertainment figures.
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd4c7888190b85c39decdb0333f |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:28 a.m.