Triple
T21664749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen Woolley |
E534684
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Woolley |
—
|
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: Woolley | Statement: [Stephen Woolley, familyName, Woolley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Woolley Context triple: [Stephen Woolley, familyName, Woolley]
-
A.
Woolley
Woolley is a small village in West Yorkshire, England, situated within the metropolitan borough of the City of Wakefield.
-
B.
Woolley
chosen
Woolley is a surname most notably associated with American actor Monty Woolley, known for his distinguished stage and film career in the mid-20th century.
-
C.
Wooley
Wooley is the surname of American actor and country-western singer Sheb Wooley, known for his hit song "The Purple People Eater" and for originating the famous "Wilhelm scream" sound effect.
-
D.
Woolsey
Woolsey is a surname most notably associated with Theodore Dwight Woolsey, a prominent 19th-century American academic and president of Yale College.
-
E.
Woollard
Woollard is a small rural village in Somerset, England, known for its picturesque setting along the River Chew and historic stone buildings.
- 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c0b26c8819092c13e59dcc3c25c |
completed | April 27, 2026, 2 p.m. |
Created at: April 16, 2026, 6:36 p.m.