Triple
T9616072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Figment |
E232222
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object |
Steve Kirk
Steve Kirk is a creator best known for developing the character Figment, the playful purple dragon associated with Disney’s Imagination! attractions.
|
E811298
|
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: Steve Kirk | Statement: [Figment, creator, Steve Kirk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Kirk Context triple: [Figment, creator, Steve Kirk]
-
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.
Kirk Stievely
Kirk Stievely is a British actor best known as the former husband of actress Victoria Tennant.
-
C.
Steve Richards
Steve Richards is a film producer known for his work on action and genre movies, including the 2010 adaptation of "The Losers."
-
D.
Steve McNiven
Steve McNiven is a Canadian comic book artist best known for his highly detailed work at Marvel Comics on major events and series such as "Civil War" and "Old Man Logan."
-
E.
Steve Speirs
Steve Speirs is a Welsh character actor known for his comedic and supporting roles in British film and television.
- 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: Steve Kirk Triple: [Figment, creator, Steve Kirk]
Generated description
Steve Kirk is a creator best known for developing the character Figment, the playful purple dragon associated with Disney’s Imagination! attractions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Steve Kirk Target entity description: Steve Kirk is a creator best known for developing the character Figment, the playful purple dragon associated with Disney’s Imagination! attractions.
-
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.
Kirk Stievely
Kirk Stievely is a British actor best known as the former husband of actress Victoria Tennant.
-
C.
Steve Richards
Steve Richards is a film producer known for his work on action and genre movies, including the 2010 adaptation of "The Losers."
-
D.
Steve McNiven
Steve McNiven is a Canadian comic book artist best known for his highly detailed work at Marvel Comics on major events and series such as "Civil War" and "Old Man Logan."
-
E.
Steve Speirs
Steve Speirs is a Welsh character actor known for his comedic and supporting roles in British film and television.
- 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_69ca84867bb88190b4b57dd5a56d5691 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9aad71a0819084ea00c2409e9922 |
completed | April 1, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18225f9508190bde23b9d2a40bccc |
completed | April 4, 2026, 9:27 p.m. |
| NEDg | Description generation | batch_69d182db3ef481908a7e588aa35a7a3f |
completed | April 4, 2026, 9:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d183481f488190ab63f0bde2d5c6fc |
completed | April 4, 2026, 9:31 p.m. |
Created at: March 30, 2026, 8:09 p.m.