Triple
T13148350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cocaine Bear |
E312397
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Jimmy Warden
Jimmy Warden is an American screenwriter best known for writing the darkly comedic horror film "Cocaine Bear."
|
E1024691
|
NE FINISHED |
How this triple was built (4 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: Jimmy Warden | Statement: [Cocaine Bear, screenwriter, Jimmy Warden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jimmy Warden Context triple: [Cocaine Bear, screenwriter, Jimmy Warden]
-
A.
Tim Warden
Tim Warden is the troubled young boy at the center of the psychological thriller film "Silent Fall," whose mysterious behavior holds the key to a brutal family murder.
-
B.
Matt Wheeler
Matt Wheeler is a television writer and producer best known for creating the science fiction drama series "Salvation."
-
C.
Peter Warrick
Peter Warrick is a former American football wide receiver best known for his standout college career at Florida State University and his subsequent tenure in the NFL with the Cincinnati Bengals.
-
D.
Jacob Ward
Jacob Ward is an actor known for his role in the film "Somewhere in Queens."
-
E.
Kyle Walters
Kyle Walters is a Canadian football executive and former player best known as the general manager of the Winnipeg Blue Bombers in the CFL.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Jimmy Warden Triple: [Cocaine Bear, screenwriter, Jimmy Warden]
Generated description
Jimmy Warden is an American screenwriter best known for writing the darkly comedic horror film "Cocaine Bear."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jimmy Warden Target entity description: Jimmy Warden is an American screenwriter best known for writing the darkly comedic horror film "Cocaine Bear."
-
A.
Tim Warden
Tim Warden is the troubled young boy at the center of the psychological thriller film "Silent Fall," whose mysterious behavior holds the key to a brutal family murder.
-
B.
Matt Wheeler
Matt Wheeler is a television writer and producer best known for creating the science fiction drama series "Salvation."
-
C.
Peter Warrick
Peter Warrick is a former American football wide receiver best known for his standout college career at Florida State University and his subsequent tenure in the NFL with the Cincinnati Bengals.
-
D.
Jacob Ward
Jacob Ward is an actor known for his role in the film "Somewhere in Queens."
-
E.
Kyle Walters
Kyle Walters is a Canadian football executive and former player best known as the general manager of the Winnipeg Blue Bombers in the CFL.
- F. None of above. chosen
Provenance (5 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98bd0f5b08190ab700c5de1c8e138 |
completed | April 10, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eae834908190aecb825db1d705ff |
completed | May 3, 2026, 6:27 a.m. |
| NEDg | Description generation | batch_69f6eb9ff2a881908004cc060b892f48 |
completed | May 3, 2026, 6:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6ec67be70819087d6c49a85d163bc |
completed | May 3, 2026, 6:34 a.m. |
Created at: April 9, 2026, 9:11 p.m.