Triple
T5424166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Secretary for Foreign Tongues |
E121321
|
entity |
| Predicate | officeHolder |
P537
|
FINISHED |
| Object | John Milton |
E22807
|
NE FINISHED |
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: John Milton | Statement: [Secretary for Foreign Tongues, officeHolder, John Milton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Milton Context triple: [Secretary for Foreign Tongues, officeHolder, John Milton]
-
A.
John Milton
chosen
John Milton was a 17th-century English poet and intellectual best known for his epic poem "Paradise Lost" and his influential political and religious writings.
-
B.
Andrew Marvell
Andrew Marvell was a 17th-century English metaphysical poet and politician best known for works such as "To His Coy Mistress" and for his role as a Parliamentarian during the English Civil War and Restoration.
-
C.
Dryden
Dryden is a small village in Tompkins County, New York, known for its rural character and proximity to the city of Ithaca.
-
D.
Dryden
Dryden is a surname most famously associated with Ken Dryden, the Hall of Fame Canadian ice hockey goaltender and former politician.
-
E.
Dryden
Dryden is a small city in northwestern Ontario, Canada, known historically for its forestry and paper mill industries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd88142b4c8190a0a9fce117aaef14 |
completed | March 20, 2026, 5:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf7fd5099081908ace06c317f6afd1 |
completed | March 22, 2026, 5:36 a.m. |
Created at: March 20, 2026, 2:06 p.m.