Triple
T20763321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minister of Militia and Defence |
E511025
|
entity |
| Predicate | officeHeldBy |
P537
|
FINISHED |
| Object | Sam Hughes |
—
|
NE NERFINISHED |
How this triple was built (2 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: Sam Hughes | Statement: [Minister of Militia and Defence, officeHeldBy, Sam Hughes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sam Hughes Context triple: [Minister of Militia and Defence, officeHeldBy, Sam Hughes]
-
A.
Sam Hughes
chosen
Sam Hughes was a controversial Canadian politician and Minister of Militia and Defence during World War I, known for his role in rapidly expanding and organizing Canada’s wartime army.
-
B.
Fred Kilgour
Fred Kilgour was an American librarian and information scientist best known for pioneering online library cataloging and founding the OCLC cooperative.
-
C.
Mackenzie Bowell
Mackenzie Bowell was a Canadian politician who served as the country’s fifth prime minister in the late 19th century and was a prominent figure in the Conservative Party.
-
D.
Jim Harris
Jim Harris is a technology executive best known as one of the founders of the computer company Compaq.
-
E.
Jim Harris
Jim Harris is a relatively common personal name shared by multiple individuals across fields such as politics, sports, and the arts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ca01148190ac018e57e0cab46f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c24a154c8190a9062923308d2411 |
completed | April 21, 2026, 12:18 a.m. |
Created at: April 16, 2026, 12:35 p.m.