Triple
T9496718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fried & True: More than 50 Recipes for America’s Best Fried Chicken and Sides |
E229025
|
entity |
| Predicate | numberOfRecipes |
P88940
|
FINISHED |
| Object | more than 50 |
—
|
LITERAL 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: more than 50 | Statement: [Fried & True: More than 50 Recipes for America’s Best Fried Chicken and Sides, numberOfRecipes, more than 50]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRecipes Context triple: [Fried & True: More than 50 Recipes for America’s Best Fried Chicken and Sides, numberOfRecipes, more than 50]
-
A.
usesRecipeOf
Indicates that one entity prepares or creates something by following the recipe or formula originally defined or used by another entity.
-
B.
numberOfRecommendations
Indicates the quantity of recommendations associated with or given to a particular entity or item.
-
C.
numberOfRestaurants
Indicates the quantitative count of restaurants associated with a given entity or context.
-
D.
numberOfJars
Indicates the quantity of jars associated with a given entity or context.
-
E.
numberOfCups
Indicates the quantity of cups associated with a given entity or context.
- F. None of above. chosen
Provenance (4 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd95ecf4148190aa8f4733980166ae |
completed | April 1, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69cca5651a588190a3cfebe249a223e5 |
completed | April 1, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69cca8c6b0f081908334d6c7cf80e03c |
completed | April 1, 2026, 5:10 a.m. |
Created at: March 30, 2026, 7:56 p.m.