Triple
T10210210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fahrenheit 451 (2018 film) |
E242305
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Peter Jaysen
Peter Jaysen is a film producer known for his work on the 2018 adaptation of Ray Bradbury’s dystopian novel "Fahrenheit 451."
|
E849577
|
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: Peter Jaysen | Statement: [Fahrenheit 451 (2018 film), producer, Peter Jaysen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Jaysen Context triple: [Fahrenheit 451 (2018 film), producer, Peter Jaysen]
-
A.
Peter Jay
Peter Jay is a British economist, broadcaster, and former ambassador to the United States, known for his influential roles in journalism and public service.
-
B.
Peter Jay
Peter Jay was a prominent New York merchant and landowner of the 18th century, best known as the father of American statesman and first Chief Justice John Jay.
-
C.
Peter Nashel
Peter Nashel is an American composer known for his film and television scores, including his work on the darkly comedic biopic "I, Tonya."
-
D.
Peter Joshua
Peter Joshua is a charming and enigmatic man who becomes entangled with Audrey Hepburn's character in the 1963 romantic mystery film "Charade."
-
E.
Peter Jacob
Peter Jacob was the first husband of German filmmaker and photographer Leni Riefenstahl.
- 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: Peter Jaysen Triple: [Fahrenheit 451 (2018 film), producer, Peter Jaysen]
Generated description
Peter Jaysen is a film producer known for his work on the 2018 adaptation of Ray Bradbury’s dystopian novel "Fahrenheit 451."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peter Jaysen Target entity description: Peter Jaysen is a film producer known for his work on the 2018 adaptation of Ray Bradbury’s dystopian novel "Fahrenheit 451."
-
A.
Peter Jay
Peter Jay was a prominent New York merchant and landowner of the 18th century, best known as the father of American statesman and first Chief Justice John Jay.
-
B.
Peter Jay
Peter Jay is a British economist, broadcaster, and former ambassador to the United States, known for his influential roles in journalism and public service.
-
C.
Peter Nashel
Peter Nashel is an American composer known for his film and television scores, including his work on the darkly comedic biopic "I, Tonya."
-
D.
Peter Joshua
Peter Joshua is a charming and enigmatic man who becomes entangled with Audrey Hepburn's character in the 1963 romantic mystery film "Charade."
-
E.
Peter Jacob
Peter Jacob was the first husband of German filmmaker and photographer Leni Riefenstahl.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d395fbed008190b66996f5bb397853 |
completed | April 6, 2026, 11:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d652cca9c081909f705365c70db009 |
completed | April 8, 2026, 1:06 p.m. |
| NEDg | Description generation | batch_69d654ddaed88190bcd7f1a2ee9dd462 |
completed | April 8, 2026, 1:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d655338cc08190ba00163f0afa4c3b |
completed | April 8, 2026, 1:16 p.m. |
Created at: April 6, 2026, 11:01 a.m.