Triple
T29186468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Govinda’s restaurant or prasadam hall |
E739880
|
entity |
| Predicate | foodClassification |
P86375
|
FINISHED |
| Object | lacto-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: lacto-vegetarian | Statement: [Govinda’s restaurant or prasadam hall, foodClassification, lacto-vegetarian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foodClassification Context triple: [Govinda’s restaurant or prasadam hall, foodClassification, lacto-vegetarian]
-
A.
foodItem
Indicates that one entity is a food item that can be eaten or used as food in relation to another entity.
-
B.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
-
C.
genreOfRecipes
Indicates that one entity is a genre or category that characterizes the type or style of recipes associated with another entity.
-
D.
primaryFoodType
chosen
Indicates the main category of food that characterizes what an entity primarily eats or serves.
-
E.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
- 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_69f07cb74c2c8190ad396487fcb4fde6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6638722fc819098f18314dfa88a6c |
completed | May 2, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, noon