Triple
T6269704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All for Love |
E140497
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Rick Timas
Rick Timas is a music producer best known for his work on the song "All for Love."
|
E579740
|
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: Rick Timas | Statement: [All for Love, producer, Rick Timas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rick Timas Context triple: [All for Love, producer, Rick Timas]
-
A.
Tim Dutton
Tim Dutton is a British actor known for his work in film, television, and theatre, including roles in period dramas and literary adaptations.
-
B.
Rick Fisher
Rick Fisher is a renowned British lighting designer known for his acclaimed work in theatre and opera productions worldwide.
-
C.
Rob Fergus
Rob Fergus is a computer scientist and researcher in machine learning and computer vision, known for his influential work in deep learning and academic leadership in AI.
-
D.
Rob Tapert
Rob Tapert is an American film and television producer best known for co-creating and producing genre series like Xena: Warrior Princess and Spartacus, as well as collaborating frequently with director Sam Raimi on horror and fantasy projects.
-
E.
Mark Sanger
Mark Sanger is a British film editor best known for his Academy Award–winning work on the science fiction thriller "Gravity."
- 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: Rick Timas Triple: [All for Love, producer, Rick Timas]
Generated description
Rick Timas is a music producer best known for his work on the song "All for Love."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rick Timas Target entity description: Rick Timas is a music producer best known for his work on the song "All for Love."
-
A.
Tim Dutton
Tim Dutton is a British actor known for his work in film, television, and theatre, including roles in period dramas and literary adaptations.
-
B.
Rick Fisher
Rick Fisher is a renowned British lighting designer known for his acclaimed work in theatre and opera productions worldwide.
-
C.
Rob Fergus
Rob Fergus is a computer scientist and researcher in machine learning and computer vision, known for his influential work in deep learning and academic leadership in AI.
-
D.
Rob Tapert
Rob Tapert is an American film and television producer best known for co-creating and producing genre series like Xena: Warrior Princess and Spartacus, as well as collaborating frequently with director Sam Raimi on horror and fantasy projects.
-
E.
Mark Sanger
Mark Sanger is a British film editor best known for his Academy Award–winning work on the science fiction thriller "Gravity."
- 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_69c008cabc4081909723e2547c9d6cc0 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063a3f1d081908ccff88db94b1f9c |
completed | March 22, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c24460f1bc8190b15ca58331410ec2 |
completed | March 24, 2026, 7:59 a.m. |
| NEDg | Description generation | batch_69c2a5a6157c8190a57a297cf606eecb |
completed | March 24, 2026, 2:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c2a60a92cc8190847e242482788ff3 |
completed | March 24, 2026, 2:56 p.m. |
Created at: March 22, 2026, 4:25 p.m.