Triple
T14741126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Cardinal McCloskey |
E346346
|
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 cardinal of the Catholic Church in the United States.
|
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 the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
-
B.
John
John is the middle name of Samuel John Mills, an American Congregationalist minister known for his role in early 19th-century missionary movements.
-
C.
John
John is the given name of John C. Sheehan, an American organic chemist renowned for achieving the first complete laboratory synthesis of penicillin.
-
D.
John
John was a Portuguese royal who held the title of Prince of Brazil and later became King John VI of Portugal.
-
E.
John
John is the given name of John Boyle O'Reilly, a 19th-century Irish-born poet, journalist, and civil rights activist who became influential in the United States.
- 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 cardinal of the Catholic Church in the United States.
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 cardinal of the Catholic Church in the United States.
-
A.
John
chosen
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.
-
B.
John
John is the given name of John Baptist Purcell, a 19th-century Irish-American Roman Catholic archbishop of Cincinnati.
-
C.
John
John is the given name of John Bird Sumner, a 19th-century Archbishop of Canterbury and influential leader of the Church of England.
-
D.
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.
-
E.
John
John is the given name of John Sentamu, the former Archbishop of York and a prominent figure in the Church of England.
- F. None of above.
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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7345680819093e901233a064e48 |
completed | April 14, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe24ac17888190bda346df75d37620 |
completed | May 8, 2026, 6 p.m. |
| NEDg | Description generation | batch_69fe357d7ae0819085ad5f31ef5722a0 |
completed | May 8, 2026, 7:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe361cd7188190adb9c57314de9276 |
completed | May 8, 2026, 7:14 p.m. |
Created at: April 10, 2026, 1:30 a.m.