Triple
T3274574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Cardinal McCloskey |
E68728
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John is the given name of John Cardinal McCloskey, the 19th-century American prelate who became the first U.S. cardinal in the Roman Catholic Church.
|
E346346
|
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: [John Cardinal McCloskey, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John Cardinal McCloskey, givenName, John]
-
A.
John
John is traditionally regarded as the author of the New Testament’s Book of Revelation, a prophetic and apocalyptic text in Christian scripture.
-
B.
John
John is the given name of John Perry Barlow, the American poet, essayist, and co-founder of the Electronic Frontier Foundation known for his advocacy of digital rights.
-
C.
John
John is the given name of John Nance Garner, who served as the 32nd vice president of the United States under President Franklin D. Roosevelt.
-
D.
John
John is the given first name of J. Michael Bishop, the American immunologist and Nobel Prize–winning scientist known for his work on oncogenes.
-
E.
John
John is the given name of John F. Sattler, likely referring to him in a more informal or abbreviated context.
- 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: [John Cardinal McCloskey, givenName, John]
Generated description
John is the given name of John Cardinal McCloskey, the 19th-century American prelate who became the first U.S. cardinal in the Roman Catholic Church.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John is the given name of John Cardinal McCloskey, the 19th-century American prelate who became the first U.S. cardinal in the Roman Catholic Church.
-
A.
John
John is the given name of John Jay, one of the Founding Fathers of the United States and the first Chief Justice of the U.S. Supreme Court.
-
B.
John
John is the given name of John Stott, a prominent 20th-century English Anglican priest, theologian, and influential evangelical leader.
-
C.
John
John is the given name of John J. Pershing, the famed American general who led the American Expeditionary Forces in World War I.
-
D.
John
John is the given name of John Foster Dulles, a prominent 20th-century American diplomat and U.S. Secretary of State during the Eisenhower administration.
-
E.
John
John is the given name of the influential American financier and banker J. P. Morgan, a central figure in early 20th-century U.S. finance and industry.
- 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adaff8a440819092509bc8511b2785 |
completed | March 8, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3bb50b48190a1d2ea0dd71c039f |
completed | March 12, 2026, 5:11 p.m. |
| NEDg | Description generation | batch_69b2f9db711c8190a6903ae530ead9ea |
completed | March 12, 2026, 5:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b312b273b48190a949e61b87722084 |
completed | March 12, 2026, 7:23 p.m. |
Created at: March 8, 2026, 3:10 p.m.