Triple
T28169505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jerusalem: A Cookbook |
E715416
|
entity |
| Predicate | featuresDishType |
P128481
|
FINISHED |
| Object | salads |
—
|
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: salads | Statement: [Jerusalem: A Cookbook, featuresDishType, salads]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresDishType Context triple: [Jerusalem: A Cookbook, featuresDishType, salads]
-
A.
foodTypeOffered
Indicates that one entity offers or serves a particular type or category of food.
-
B.
genreOfRecipes
chosen
Indicates that one entity is a genre or category that characterizes the type or style of recipes associated with another entity.
-
C.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
D.
dishVariation
Indicates that one dish is a variation, adaptation, or modified version of another dish.
-
E.
hasDishType
Indicates that an item (such as a food or menu entry) is classified as belonging to a particular type of dish (e.g., appetizer, main course, dessert).
- 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_69efd6b340f0819095680e15dcdc1830 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69fe1fd637c08190aa95cd2478c278cb |
completed | May 8, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69fe19344bb481909b5e2144155e4add |
completed | May 8, 2026, 5:11 p.m. |
Created at: April 27, 2026, 10:11 p.m.