Triple
T21038428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke Pearson |
E518253
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Jeannine |
—
|
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: Jeannine | Statement: [Duke Pearson, notableWork, Jeannine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeannine Context triple: [Duke Pearson, notableWork, Jeannine]
-
A.
Janeane
Janeane is a female given name most notably associated with American comedian and actress Janeane Garofalo.
-
B.
Janine
chosen
Janine is a feminine given name used in various cultures, often as a variant of Jeanine or Jeanne.
-
C.
Jeanie
Jeanie is a female given name, often used as a diminutive of Jean or Jeanne.
-
D.
Jeanette
Jeanette is the given name of Jennie Jerome, the American-born British socialite best known as the mother of Winston Churchill.
-
E.
Jeanette
Jeanette is the given first name of American actress Peggy Moran, known for her roles in 1930s and 1940s Hollywood films.
- 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_69e0b50438e08190917e2538bb8bc034 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fcee13b08190a8b3372f6759cd1b |
completed | April 21, 2026, 4:28 a.m. |
Created at: April 16, 2026, 2:12 p.m.