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.