Triple
T18027456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweatsuit |
E431295
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Phil Duckett
Phil Duckett is a music producer known for his work on the track "Sweatsuit."
|
E1304808
|
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: Phil Duckett | Statement: [Sweatsuit, producer, Phil Duckett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phil Duckett Context triple: [Sweatsuit, producer, Phil Duckett]
-
A.
Steve Judd
Steve Judd is the aging, principled former lawman at the heart of the Western film "Ride the High Country," whose moral integrity drives the story’s central conflict.
-
B.
David Duffield
David Duffield is an American billionaire entrepreneur and philanthropist best known for founding the enterprise software companies PeopleSoft and Workday.
-
C.
Phil Brent
Phil Brent is a fictional character from the soap opera "All My Children," known for his complex family relationships and dramatic storylines.
-
D.
Michael Buckland
Michael Buckland is an American information scientist and librarian known for his influential work on information retrieval, library services, and the theory of information systems.
-
E.
Brian G. Hutton
Brian G. Hutton was an American film director and actor best known for helming popular war and action films in the late 1960s and early 1970s.
- 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: Phil Duckett Triple: [Sweatsuit, producer, Phil Duckett]
Generated description
Phil Duckett is a music producer known for his work on the track "Sweatsuit."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Phil Duckett Target entity description: Phil Duckett is a music producer known for his work on the track "Sweatsuit."
-
A.
Steve Judd
Steve Judd is the aging, principled former lawman at the heart of the Western film "Ride the High Country," whose moral integrity drives the story’s central conflict.
-
B.
David Duffield
David Duffield is an American billionaire entrepreneur and philanthropist best known for founding the enterprise software companies PeopleSoft and Workday.
-
C.
Phil Brent
Phil Brent is a fictional character from the soap opera "All My Children," known for his complex family relationships and dramatic storylines.
-
D.
Michael Buckland
Michael Buckland is an American information scientist and librarian known for his influential work on information retrieval, library services, and the theory of information systems.
-
E.
Brian G. Hutton
Brian G. Hutton was an American film director and actor best known for helming popular war and action films in the late 1960s and early 1970s.
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b9c7be308190af0d77c0df6d94ce |
completed | April 19, 2026, 11:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a035d7ec324819099a074f6f5066190 |
completed | May 12, 2026, 5:03 p.m. |
| NEDg | Description generation | batch_6a0361aa77808190a9fb298cf1b3b785 |
completed | May 12, 2026, 5:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a036203e7e8819094e6bbb40b79e533 |
completed | May 12, 2026, 5:23 p.m. |
Created at: April 10, 2026, 10:25 a.m.