Triple
T5317646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Decoy Bride |
E121589
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Mark Aiken
Mark Aiken is an actor known for his role in the romantic comedy film "The Decoy Bride."
|
E526110
|
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: Mark Aiken | Statement: [The Decoy Bride, castMember, Mark Aiken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Aiken Context triple: [The Decoy Bride, castMember, Mark Aiken]
-
A.
Chris Ridenhour
Chris Ridenhour is a film composer known for scoring numerous low-budget genre movies, including works produced by The Asylum.
-
B.
Phil Wenneck
Phil Wenneck is a charismatic, fast-talking schoolteacher and member of the "Wolfpack" whose misadventures drive much of the comedy in The Hangover film series.
-
C.
Sean Kenney
Sean Kenney is an American actor best known for playing the disfigured Captain Christopher Pike in the original Star Trek series.
-
D.
Michael Potts
Michael Potts is an American actor known for his work in film, television, and theater, including notable roles in projects like "The Wire," "True Detective," and various Broadway productions.
-
E.
Phil Burke
Phil Burke is a Canadian actor best known for his role as Mickey McGinnes on the television drama series "Hell on Wheels."
- 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: Mark Aiken Triple: [The Decoy Bride, castMember, Mark Aiken]
Generated description
Mark Aiken is an actor known for his role in the romantic comedy film "The Decoy Bride."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mark Aiken Target entity description: Mark Aiken is an actor known for his role in the romantic comedy film "The Decoy Bride."
-
A.
Chris Ridenhour
Chris Ridenhour is a film composer known for scoring numerous low-budget genre movies, including works produced by The Asylum.
-
B.
Phil Wenneck
Phil Wenneck is a charismatic, fast-talking schoolteacher and member of the "Wolfpack" whose misadventures drive much of the comedy in The Hangover film series.
-
C.
Sean Kenney
Sean Kenney is an American actor best known for playing the disfigured Captain Christopher Pike in the original Star Trek series.
-
D.
Michael Potts
Michael Potts is an American actor known for his work in film, television, and theater, including notable roles in projects like "The Wire," "True Detective," and various Broadway productions.
-
E.
Phil Burke
Phil Burke is a Canadian actor best known for his role as Mickey McGinnes on the television drama series "Hell on Wheels."
- 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_69bd463d956c819088105c3db802c017 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd855269ac8190bb7a9248d04f1823 |
completed | March 20, 2026, 5:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfabe6de448190a4e0c2e537a2e045 |
completed | March 22, 2026, 8:44 a.m. |
| NEDg | Description generation | batch_69bfadf4a0bc8190a53265127e5e5cf8 |
completed | March 22, 2026, 8:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bfae4cc484819089e42b82e5638d0c |
completed | March 22, 2026, 8:54 a.m. |
Created at: March 20, 2026, 1:59 p.m.