Triple
T34150682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamika Ekadashi |
E875984
|
entity |
| Predicate | recommendedFood |
P7171
|
FINISHED |
| Object | simple sattvic food |
—
|
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: simple sattvic food | Statement: [Kamika Ekadashi, recommendedFood, simple sattvic food]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recommendedFood Context triple: [Kamika Ekadashi, recommendedFood, simple sattvic food]
-
A.
intendedFood
Indicates that one entity is the food item that another entity plans or is meant to eat or consume.
-
B.
servingRecommendation
Indicates a suggested or advised quantity, manner, or context in which something should be served.
-
C.
foodCustom
chosen
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
-
D.
storesFood
Indicates that one entity keeps or holds food items for future use or consumption.
-
E.
dietaryOptions
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_69f349abaa508190a820f206620efddc |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:54 a.m.