Triple
T21093642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RJ Cyler |
E519701
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | I’m Dying Up Here |
—
|
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: I’m Dying Up Here | Statement: [RJ Cyler, notableWork, I’m Dying Up Here]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: I’m Dying Up Here Context triple: [RJ Cyler, notableWork, I’m Dying Up Here]
-
A.
I’m Dying Up Here
chosen
"I’m Dying Up Here" is a dark comedy-drama television series that explores the lives and struggles of stand-up comedians in the 1970s Los Angeles comedy scene.
-
B.
If You Want to Die in Bed
"If You Want to Die in Bed" is a darkly comic solo number from the musical *Miss Saigon* in which the Engineer reflects cynically on survival and self-interest during the Vietnam War.
-
C.
You’re Gonna Die
"You’re Gonna Die" is a work by the experimental noise rock band Destroy All Monsters, reflecting their abrasive, avant-garde style and underground art-punk sensibilities.
-
D.
We in Here
"We in Here" is a hip-hop track featured on the album "Year of the Dog... Again" by DMX.
-
E.
Dyin’ Day
"Dyin’ Day" is a song by guitarist Steve Vai featured on his 1996 album *Fire Garden*.
- 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_69e0b507dd9081908fb8bfcbef4c8b46 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e70950a31c8190bde2d7b414c362c7 |
completed | April 21, 2026, 5:21 a.m. |
Created at: April 16, 2026, 2:51 p.m.