Triple
T11411343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald David Coryell |
E270378
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Donald
Donald is the given name of Donald David Coryell, the innovative American football coach known for revolutionizing the passing game in the NFL.
|
E925324
|
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: Donald | Statement: [Donald David Coryell, givenName, Donald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donald Context triple: [Donald David Coryell, givenName, Donald]
-
A.
Donald
Donald is the surname of Aaron Donald, the dominant American football defensive tackle widely regarded as one of the greatest defensive players in NFL history.
-
B.
Donald
Donald is a fictional character portrayed by American actor Matt Bomer, likely in a film or television production.
-
C.
Donald
Donald is the given first name of influential American jazz musician, arranger, and bandleader Don Redman.
-
D.
Donald
Donald is the given first name of American actor Don Cheadle, known for his acclaimed film and television roles.
-
E.
Donald
Donald is the given first name of Don Granato, an American professional ice hockey coach.
- 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: Donald Triple: [Donald David Coryell, givenName, Donald]
Generated description
Donald is the given name of Donald David Coryell, the innovative American football coach known for revolutionizing the passing game in the NFL.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Donald Target entity description: Donald is the given name of Donald David Coryell, the innovative American football coach known for revolutionizing the passing game in the NFL.
-
A.
Donald
Donald is the given first name of Don Hutson, a pioneering American football wide receiver widely regarded as one of the NFL’s earliest superstars.
-
B.
Donald
Donald is the given name of Don Revie, the renowned English football player and manager best known for his successful tenure at Leeds United.
-
C.
Donald
Donald is the surname of Aaron Donald, the dominant American football defensive tackle widely regarded as one of the greatest defensive players in NFL history.
-
D.
Donald
Donald is the given name of Donald Trump, the 45th president of the United States and a prominent businessman and media personality.
-
E.
Donald
Donald is the given first name of Neil Johnston, an American Basketball Hall of Famer known for his prolific scoring in the 1950s NBA.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8015017d08190b4020c76545556d6 |
completed | April 9, 2026, 7:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5b855f0508190a2e57ef9407ddb1a |
completed | April 20, 2026, 5:23 a.m. |
| NEDg | Description generation | batch_69e5c289b5ac81909bdaec61a66f6654 |
completed | April 20, 2026, 6:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5c43f4b4c8190aeae600364d2e4ac |
completed | April 20, 2026, 6:14 a.m. |
Created at: April 8, 2026, 9:34 p.m.