Triple
T20009410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John William Friso |
E494546
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object | William |
—
|
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: William | Statement: [John William Friso, middleName, William]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Context triple: [John William Friso, middleName, William]
-
A.
William
chosen
William is a common masculine given name of Germanic origin, widely used in English-speaking countries.
-
B.
Thomas
Thomas is the given name of Thomas Fairfax, 1st Lord Fairfax of Cameron, a prominent Parliamentarian general during the English Civil War.
-
C.
Thomas
Thomas is the given name of Thomas Fairfax, 2nd Lord Fairfax of Cameron, a prominent Parliamentary general during the English Civil War.
-
D.
Thomas
Thomas is the given first name of American actor Tom Sizemore, known for his intense supporting roles in crime and war films.
-
E.
Thomas
Thomas is the given first name of American comedian and actor Tim Conway, known for his work on "The Carol Burnett Show."
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a81c5881909692fcaaf59a57c9 |
completed | April 20, 2026, 5:26 p.m. |
Created at: April 11, 2026, 3:33 p.m.