Triple
T14169745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paddy Driscoll |
E351174
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John is the first name of American football player and coach Paddy Driscoll, a Pro Football Hall of Famer known for his versatility and early NFL success.
|
E1083649
|
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: John | Statement: [Paddy Driscoll, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [Paddy Driscoll, givenName, John]
-
A.
John
John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
-
B.
John
John Ross is a personal name shared by various notable individuals across history, including leaders, politicians, and public figures.
-
C.
John
John of Görlitz was a 14th-century German prince of the House of Luxembourg who held the title of Duke of Görlitz.
-
D.
John
John is the given name of John C. Sheehan, an American organic chemist renowned for achieving the first complete laboratory synthesis of penicillin.
-
E.
John
John is the first name of Jack Phillips, the British wireless operator on the RMS Titanic who died during its sinking in 1912.
- 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: John Triple: [Paddy Driscoll, givenName, John]
Generated description
John is the first name of American football player and coach Paddy Driscoll, a Pro Football Hall of Famer known for his versatility and early NFL success.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John is the first name of American football player and coach Paddy Driscoll, a Pro Football Hall of Famer known for his versatility and early NFL success.
-
A.
John
John is the first name of American college football coach Jimbo Fisher, known for leading Florida State University to a national championship.
-
B.
John
John is the given name of John Madden, the famed American football coach, broadcaster, and namesake of the Madden NFL video game series.
-
C.
John
John is the given first name of Johnny Lujack, a notable American football quarterback and Heisman Trophy winner.
-
D.
John
John is the first name of former NFL quarterback Joey Harrington, who played primarily for the Detroit Lions in the early 2000s.
-
E.
John
John is the given name of John David Crow, a celebrated American football player and Heisman Trophy winner.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b472288190b4a271daa54aa6cd |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7d863ac819085bf5cd76cb2e8dd |
completed | May 7, 2026, 8:36 p.m. |
| NEDg | Description generation | batch_69fd0070ded48190a2cd1a1f95a48d13 |
completed | May 7, 2026, 9:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd012728788190b45639644e83afee |
completed | May 7, 2026, 9:16 p.m. |
Created at: April 10, 2026, 1:01 a.m.