Triple
T3882784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mastering the Art of French Cooking |
E92862
|
entity |
| Predicate | hasRecipeType |
P16808
|
FINISHED |
| Object | sauces |
—
|
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: sauces | Statement: [Mastering the Art of French Cooking, hasRecipeType, sauces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecipeType Context triple: [Mastering the Art of French Cooking, hasRecipeType, sauces]
-
A.
usesRecipeOf
Indicates that one entity prepares or creates something by following the recipe or formula originally defined or used by another entity.
-
B.
haveType
chosen
Indicates that an entity belongs to or is classified under a specified type or category.
-
C.
hasFormulationType
Indicates the specific way something is physically prepared or presented, such as its dosage form, composition, or delivery format.
-
D.
hasMaterialType
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
E.
isCookedBy
Indicates that something has been prepared or made ready for eating through cooking by a particular agent.
- F. None of above.
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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.