Triple
T22905472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Death Race for Love |
E568432
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Robbery |
—
|
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: Robbery | Statement: [Death Race for Love, hasTrack, Robbery]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robbery Context triple: [Death Race for Love, hasTrack, Robbery]
-
A.
Robbery
chosen
"Robbery" is a popular emo-rap song by Juice WRLD known for its melodic delivery and themes of heartbreak and emotional turmoil.
-
B.
Robbery
"Robbery" is a 1967 British crime film directed by Peter Yates, known for its gritty depiction of a heist inspired by the Great Train Robbery and for starring Stanley Baker.
-
C.
Armored Car Robbery
Armored Car Robbery is a 1950 American film noir crime thriller centered on a meticulously planned armored car heist and its violent aftermath.
-
D.
Robbery Under Arms
Robbery Under Arms is a 1957 British crime film adaptation of Rolf Boldrewood’s classic Australian bushranger novel, featuring Maureen Swanson among its principal cast.
-
E.
The Robbery
"The Robbery" is an episode of the sitcom *Seinfeld*, continuing the early misadventures of Jerry and his friends in New York City.
- 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_69e2458cd9e48190943ad2e34485d939 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f180198fe88190b2f8c2a827d95fdc |
completed | April 29, 2026, 3:50 a.m. |
Created at: April 17, 2026, 3:41 p.m.