Triple
T21554974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walters |
E531865
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Charles Walters |
—
|
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: Charles Walters | Statement: [Walters, hasNotableBearer, Charles Walters]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charles Walters Context triple: [Walters, hasNotableBearer, Charles Walters]
-
A.
Charles Walters
chosen
Charles Walters was an American film director and choreographer best known for his work on classic MGM musicals in the mid-20th century.
-
B.
Don Walters
Don Walters is an American local politician who serves as the mayor of Cuyahoga Falls, Ohio.
-
C.
Dan Woolsey
Dan Woolsey is an entrepreneur and media professional best known as a founder of the African American–focused news and entertainment platform TheGrio.
-
D.
Walter Sillers
Walter Sillers was a prominent Mississippi political figure whose influence and legacy in the state led to major public buildings being named in his honor.
-
E.
Paul Lovett
Paul Lovett is a film screenwriter best known for co-writing the action drama movie "Four Brothers."
- 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_69e0c460232c81908de2c3819d17c00e |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eed2de1c248190b303a4a55b022374 |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 16, 2026, 6:29 p.m.