Triple
T12992111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L.A. Takedown |
E321930
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Scott Plank
Scott Plank was an American film and television actor known for his roles in crime dramas and action projects during the 1980s and 1990s.
|
E1014226
|
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: Scott Plank | Statement: [L.A. Takedown, hasCastMember, Scott Plank]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scott Plank Context triple: [L.A. Takedown, hasCastMember, Scott Plank]
-
A.
Doug Plank
Doug Plank is a former NFL safety for the Chicago Bears who later became a successful arena football coach.
-
B.
Sean Plaice
Sean Plaice is an entrepreneur best known as a co-founder of the on-demand delivery service Postmates.
-
C.
Jon Plowman
Jon Plowman is a British television producer best known for his influential work on BBC comedies, including series such as Absolutely Fabulous and The Office.
-
D.
Matt Wolpert
Matt Wolpert is a television writer and producer best known for co-creating the alternate-history space drama series "For All Mankind."
-
E.
Keith Poulson
Keith Poulson is an American actor known for his work in independent films and for roles in offbeat, character-driven movies.
- 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: Scott Plank Triple: [L.A. Takedown, hasCastMember, Scott Plank]
Generated description
Scott Plank was an American film and television actor known for his roles in crime dramas and action projects during the 1980s and 1990s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Scott Plank Target entity description: Scott Plank was an American film and television actor known for his roles in crime dramas and action projects during the 1980s and 1990s.
-
A.
Doug Plank
Doug Plank is a former NFL safety for the Chicago Bears who later became a successful arena football coach.
-
B.
Sean Plaice
Sean Plaice is an entrepreneur best known as a co-founder of the on-demand delivery service Postmates.
-
C.
Jon Plowman
Jon Plowman is a British television producer best known for his influential work on BBC comedies, including series such as Absolutely Fabulous and The Office.
-
D.
Matt Wolpert
Matt Wolpert is a television writer and producer best known for co-creating the alternate-history space drama series "For All Mankind."
-
E.
Keith Poulson
Keith Poulson is an American actor known for his work in independent films and for roles in offbeat, character-driven movies.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e7765788190a9503ef055bc30ca |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8fb70f481908a9a4ca04d6bf93b |
completed | May 3, 2026, 2:54 a.m. |
| NEDg | Description generation | batch_69f6baa76e8c8190b84fd31657ef3385 |
completed | May 3, 2026, 3:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6bb8216fc8190a0119d434adf13a5 |
completed | May 3, 2026, 3:05 a.m. |
Created at: April 9, 2026, 8:43 p.m.