Triple
T18145161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | $40 a Day |
E434369
|
entity |
| Predicate | presenter |
P83
|
FINISHED |
| Object | Rachael Ray |
—
|
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: Rachael Ray | Statement: [$40 a Day, presenter, Rachael Ray]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rachael Ray Context triple: [$40 a Day, presenter, Rachael Ray]
-
A.
Rachel Ray
"Rachel Ray" is a 19th-century novel by Anthony Trollope that explores themes of love, religious influence, and social pressure in a small English town.
-
B.
Rachel Ray
chosen
Rachael Ray is an American television personality, celebrity chef, and author best known for her quick and easy cooking style and shows like "30 Minute Meals."
-
C.
Sandra Lee
Sandra Lee is an American dermatologist and television personality best known for her viral pimple-popping videos and her TLC reality series "Dr. Pimple Popper."
-
D.
Sandra Lee
Sandra Lee is an American television chef and author known for her "Semi-Homemade" cooking concept and numerous Food Network shows.
-
E.
Ina Garten
Ina Garten is an American cookbook author and television host best known for her approachable, elegant home cooking showcased on the Food Network.
- 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de32d3f88190bd9f406729716407 |
completed | April 19, 2026, 1:52 p.m. |
Created at: April 10, 2026, 10:29 a.m.