Triple
T12374397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masterminds |
E295084
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Chris Bowman
Chris Bowman is a screenwriter best known for co-writing the comedy heist film "Masterminds."
|
E988336
|
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: Chris Bowman | Statement: [Masterminds, screenwriter, Chris Bowman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris Bowman Context triple: [Masterminds, screenwriter, Chris Bowman]
-
A.
Will Bowman
Will Bowman is the central protagonist of the science fiction television series "Colony," a former FBI agent navigating life under alien occupation while secretly working with the resistance.
-
B.
John Bowman
John Bowman was a 19th-century American politician who served in a key statewide infrastructure and regulatory role in New York.
-
C.
Lee Bowman
Lee Bowman was an American film and television actor active from the 1930s to the 1950s, known for his suave leading-man roles in Hollywood productions.
-
D.
John Bryan Bowman
John Bryan Bowman was a 19th-century American educator and civic leader best known for establishing what would become the University of Kentucky.
-
E.
Ky Bowman
Ky Bowman is an American professional basketball player and former standout point guard for Boston College who has played in the NBA and overseas.
- 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: Chris Bowman Triple: [Masterminds, screenwriter, Chris Bowman]
Generated description
Chris Bowman is a screenwriter best known for co-writing the comedy heist film "Masterminds."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chris Bowman Target entity description: Chris Bowman is a screenwriter best known for co-writing the comedy heist film "Masterminds."
-
A.
Will Bowman
Will Bowman is the central protagonist of the science fiction television series "Colony," a former FBI agent navigating life under alien occupation while secretly working with the resistance.
-
B.
John Bowman
John Bowman was a 19th-century American politician who served in a key statewide infrastructure and regulatory role in New York.
-
C.
Lee Bowman
Lee Bowman was an American film and television actor active from the 1930s to the 1950s, known for his suave leading-man roles in Hollywood productions.
-
D.
John Bryan Bowman
John Bryan Bowman was a 19th-century American educator and civic leader best known for establishing what would become the University of Kentucky.
-
E.
Ky Bowman
Ky Bowman is an American professional basketball player and former standout point guard for Boston College who has played in the NBA and overseas.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93fa8ca7c8190b3f8e9c2ec23e837 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64b926c5c81909427eb191ae75ec6 |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64da25bf88190889273bf41e2f154 |
completed | May 2, 2026, 7:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f65213ed84819086fda178aaf9e774 |
completed | May 2, 2026, 7:35 p.m. |
Created at: April 8, 2026, 9:54 p.m.