Triple
T11365730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J. Gresham Machen |
E269199
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John is the given name of J. Gresham Machen, an influential early 20th-century American Presbyterian theologian and New Testament scholar.
|
E921626
|
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: [J. Gresham Machen, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [J. Gresham Machen, givenName, John]
-
A.
John
John is the nickname of John Riggins, a former American football running back best known for his Hall of Fame career with the Washington Redskins in the NFL.
-
B.
John
John is the given name of John Arbuthnot Fisher, a prominent British admiral and naval reformer of the late 19th and early 20th centuries.
-
C.
John
John is the given name of the American composer John Luther Adams, known for his works inspired by nature and environmental themes.
-
D.
John
John is the given first name of American character actor and comedian Rags Ragland.
-
E.
John
John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
- 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: [J. Gresham Machen, givenName, John]
Generated description
John is the given name of J. Gresham Machen, an influential early 20th-century American Presbyterian theologian and New Testament scholar.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John is the given name of J. Gresham Machen, an influential early 20th-century American Presbyterian theologian and New Testament scholar.
-
A.
John
John is the given name of John Stott, a prominent 20th-century English Anglican priest, theologian, and influential evangelical leader.
-
B.
John
John is the given name of John Howard Yoder, an influential American Mennonite theologian known for his work on Christian pacifism and ethics.
-
C.
John
John is the given first name of the 19th-century English theologian and social reformer Frederick Denison Maurice.
-
D.
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.
-
E.
John
John is the given name of John Milton Gregory, a 19th-century American educator and university president known for helping to found the University of Illinois.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea88558c8190aa18881af51a7b96 |
completed | April 9, 2026, 6:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e55667d4908190b6290135eba41e54 |
completed | April 19, 2026, 10:25 p.m. |
| NEDg | Description generation | batch_69e562c6e7c8819098d22a6e0daa4a51 |
completed | April 19, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e56a472f0c819086c1cccaa5ca0ae7 |
completed | April 19, 2026, 11:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.