Triple
T10942970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisa Askey |
E258520
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Dade Faison |
E905353
|
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: Dade Faison | Statement: [Lisa Askey, relative, Dade Faison]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dade Faison Context triple: [Lisa Askey, relative, Dade Faison]
-
A.
Dade Faison
chosen
Dade Faison is one of the children of actor Donald Faison and his former partner Lisa Askey.
-
B.
Leon Durham
Leon Durham is a former Major League Baseball first baseman and outfielder best known for his years with the Chicago Cubs in the early 1980s.
-
C.
Terry Fagan
Terry Fagan is an Irish social historian and community activist known for preserving and documenting the social history of Dublin’s inner city.
-
D.
Dale Tremont
Dale Tremont is the glamorous and witty fashion model portrayed by Ginger Rogers in the 1935 musical film "Top Hat."
-
E.
John Rhea
John Rhea was an early American statesman and U.S. Congressman from Tennessee who played a significant role in the state's formative political history.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770c3fb388190a598f89ae59a7b51 |
completed | April 9, 2026, 9:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4418e52f8819096c75e6e866fecef |
completed | April 19, 2026, 2:44 a.m. |
Created at: April 8, 2026, 9:23 p.m.