Triple
T9677807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | At My Table: Vegetarian Feasts for Family and Friends |
E234202
|
entity |
| Predicate | dietaryFocus |
P34157
|
FINISHED |
| Object | vegetarian |
—
|
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: vegetarian | Statement: [At My Table: Vegetarian Feasts for Family and Friends, dietaryFocus, vegetarian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dietaryFocus Context triple: [At My Table: Vegetarian Feasts for Family and Friends, dietaryFocus, vegetarian]
-
A.
nutritionType
Indicates the specific category or kind of nutritional characteristic or value associated with an entity.
-
B.
dietVersion
Indicates that one diet is a specific version, variant, or iteration of another diet.
-
C.
focusesOnNutrition
Indicates that the subject’s primary attention, activity, or content is centered on nutrition-related topics, practices, or goals.
-
D.
diet
Indicates that an entity regularly consumes a particular type or range of food as its primary source of nutrition.
-
E.
dietaryOptions
chosen
Indicates the types of diets or food-related preferences, restrictions, or choices that are applicable to or offered for an entity.
- 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_69ca84c99e34819092e5563a7106cfca |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9c9b01708190aaf51cf4d36015a0 |
completed | April 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b5d40c8190850ad7a351445f32 |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:16 p.m.