Triple
T3121851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cooke |
E65201
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Dennis Cooke
Dennis Cooke is a person notable enough to be recognized as a namesake of the surname Cooke.
|
E375436
|
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: Dennis Cooke | Statement: [Cooke, hasNotableBearer, Dennis Cooke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dennis Cooke Context triple: [Cooke, hasNotableBearer, Dennis Cooke]
-
A.
Denis Barnett
Denis Barnett was a senior Royal Air Force officer who rose to high command during and after the Second World War.
-
B.
Dennis Port
Dennis Port is a coastal village in the town of Dennis on Cape Cod, Massachusetts, known for its beaches and seaside tourism.
-
C.
Dennis Sharp
Dennis Sharp was a British architect, historian, and critic known for his influential writings on modern architecture and his work in architectural education.
-
D.
Gordon Dines
Gordon Dines was a British cinematographer known for his work on mid-20th-century films, particularly comedies and dramas.
-
E.
Ken Coleman
Ken Coleman was an American sportscaster best known for his long career calling Major League Baseball and NFL games on radio and television, particularly for the Boston Red Sox and Cleveland Browns.
- 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: Dennis Cooke Triple: [Cooke, hasNotableBearer, Dennis Cooke]
Generated description
Dennis Cooke is a person notable enough to be recognized as a namesake of the surname Cooke.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dennis Cooke Target entity description: Dennis Cooke is a person notable enough to be recognized as a namesake of the surname Cooke.
-
A.
Denis Barnett
Denis Barnett was a senior Royal Air Force officer who rose to high command during and after the Second World War.
-
B.
Dennis Port
Dennis Port is a coastal village in the town of Dennis on Cape Cod, Massachusetts, known for its beaches and seaside tourism.
-
C.
Dennis Sharp
Dennis Sharp was a British architect, historian, and critic known for his influential writings on modern architecture and his work in architectural education.
-
D.
Gordon Dines
Gordon Dines was a British cinematographer known for his work on mid-20th-century films, particularly comedies and dramas.
-
E.
Ken Coleman
Ken Coleman was an American sportscaster best known for his long career calling Major League Baseball and NFL games on radio and television, particularly for the Boston Red Sox and Cleveland Browns.
- 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_69ad8580c72481909672d37acf647893 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada52ab05c819088204bbb608c837c |
completed | March 8, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44ecf7808819096b183a0696376b6 |
completed | March 13, 2026, 5:52 p.m. |
| NEDg | Description generation | batch_69b4524337248190b8d3237ce776c398 |
completed | March 13, 2026, 6:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b46137f76481908682665dce6514d0 |
completed | March 13, 2026, 7:10 p.m. |
Created at: March 8, 2026, 3:04 p.m.