Triple
T19966546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank William Taussig |
E479949
|
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: [Frank William Taussig, middleName, William]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Context triple: [Frank William Taussig, 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 Cranmer, the 16th-century Archbishop of Canterbury and a leading figure in the English Reformation.
-
C.
Thomas
Thomas is the given name of Thomas Fairfax, 1st Lord Fairfax of Cameron, a prominent Parliamentarian general during the English Civil War.
-
D.
Thomas
Thomas is the given name of Thomas Fairfax, 2nd Lord Fairfax of Cameron, a prominent Parliamentary general during the English Civil War.
-
E.
Thomas
Thomas Savile, 1st Earl of Sussex, was a 17th-century English nobleman and politician who held prominent titles and influence during the reign of Charles I.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bc5e41881908c1e8867820f1c0c |
completed | April 20, 2026, 5 p.m. |
Created at: April 10, 2026, 1:54 p.m.