Triple
T5747172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Graves Simcoe |
E126763
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John is the given name of John Graves Simcoe, the first Lieutenant Governor of Upper Canada and a key figure in early Canadian colonial administration.
|
E545379
|
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 Graves Simcoe, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John Graves Simcoe, givenName, John]
-
A.
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.
-
B.
John
John is the given name of the American composer John Luther Adams, known for his works inspired by nature and environmental themes.
-
C.
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."
-
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: [John Graves Simcoe, givenName, John]
Generated description
John is the given name of John Graves Simcoe, the first Lieutenant Governor of Upper Canada and a key figure in early Canadian colonial administration.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John is the given name of John Graves Simcoe, the first Lieutenant Governor of Upper Canada and a key figure in early Canadian colonial administration.
-
A.
John
John is the given name of John Sandfield Macdonald, a 19th-century Canadian politician who served as the first Premier of Ontario.
-
B.
John
John is the given name of John A. Macdonald, the first prime minister of Canada and a key figure in the country's Confederation.
-
C.
John
John is the given name of Sir John Colborne, a British Army officer and colonial administrator who served as Lieutenant Governor of Upper Canada and later as Lord Seaton.
-
D.
John
John is the first name of John Tory, a Canadian politician and former mayor of Toronto.
-
E.
John
John is the given name of Sir John Anderson, a British civil servant and politician who played a key role in government during the early 20th century.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02885b0288190835809681a364b1f |
completed | March 22, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07ddd0f248190a796055212284542 |
completed | March 22, 2026, 11:40 p.m. |
| NEDg | Description generation | batch_69c08a536ecc8190a4a0391e28076d44 |
completed | March 23, 2026, 12:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c08ad660688190b5d3563ac2a9d0d9 |
completed | March 23, 2026, 12:35 a.m. |
Created at: March 22, 2026, 3:48 p.m.