Triple
T4487944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phil Woolpert |
E107293
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Phil Woolpert |
E107293
|
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: Phil Woolpert | Statement: [Phil Woolpert, name, Phil Woolpert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phil Woolpert Context triple: [Phil Woolpert, name, Phil Woolpert]
-
A.
Phil Woolpert
chosen
Phil Woolpert was a prominent American college basketball coach best known for leading the University of San Francisco to multiple national championships in the 1950s.
-
B.
Ian Walters
Ian Walters was a British sculptor best known for his politically engaged public monuments, including prominent statues of anti-apartheid leader Nelson Mandela.
-
C.
Graham Carr
Graham Carr is a Canadian academic and administrator who serves as the president of Concordia University in Montreal.
-
D.
Alan Wheatley
Alan Wheatley was a British actor best known for his stage and screen work, including his portrayal of the Sheriff of Nottingham in the 1950s television series "The Adventures of Robin Hood."
-
E.
Steven Pemberton
Steven Pemberton is a British computer scientist and software engineer known for his work on programming languages, web standards, and contributions to the development of ABC and early Python influences.
- 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd52abddf88190b4fb09884ed62500 |
completed | March 20, 2026, 1:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd6f7f33d08190a247e956193c7eef |
completed | March 20, 2026, 4:02 p.m. |
Created at: March 20, 2026, 12:59 p.m.