Triple
T9437606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samuel John Mills |
E227552
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object |
John
John is the middle name of Samuel John Mills, an American Congregationalist minister known for his role in early 19th-century missionary movements.
|
E799967
|
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: [Samuel John Mills, middleName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [Samuel John Mills, middleName, John]
-
A.
John
John is the given name of the American composer John Luther Adams, known for his works inspired by nature and environmental themes.
-
B.
John
John is the given name of John Adams, the prominent American minimalist and post-minimalist composer known for works like "Nixon in China" and "Short Ride in a Fast Machine."
-
C.
John
John is the first name of John Dashwood, a character in Jane Austen's novel "Sense and Sensibility."
-
D.
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.
-
E.
John
John is the first name of the fictional character John Connor, the prophesied leader of the human resistance in the Terminator franchise.
- 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: [Samuel John Mills, middleName, John]
Generated description
John is the middle name of Samuel John Mills, an American Congregationalist minister known for his role in early 19th-century missionary movements.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John is the middle name of Samuel John Mills, an American Congregationalist minister known for his role in early 19th-century missionary movements.
-
A.
John
John is the given name of the 19th-century British philosopher and political economist John Stuart Mill, a key figure in liberal thought and utilitarianism.
-
B.
John
John is the middle name of Sir William John Kilpatrick, an influential American educator and proponent of progressive education.
-
C.
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.
-
D.
John
John is the given name of John Fletcher Hurst, an American Methodist bishop and theologian known for his contributions to religious scholarship in the 19th century.
-
E.
John
John is the given name of John Stott, a prominent 20th-century English Anglican priest, theologian, and influential evangelical leader.
- 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_69ca8437a7ac81908651de48f2d2141d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7edff5e881909b72976e8909ba4b |
completed | April 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1104a002481909ca805893bac61c6 |
completed | April 4, 2026, 1:21 p.m. |
| NEDg | Description generation | batch_69d110ffda7881908e4edd692b818464 |
completed | April 4, 2026, 1:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d11190dd6c8190b6318df44daa9858 |
completed | April 4, 2026, 1:26 p.m. |
Created at: March 30, 2026, 7:50 p.m.