Triple
T7308620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Assamese cuisine |
E168037
|
entity |
| Predicate | cookingStyle |
P73154
|
FINISHED |
| Object | simple techniques |
—
|
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 techniques | Statement: [Assamese cuisine, cookingStyle, simple techniques]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cookingStyle Context triple: [Assamese cuisine, cookingStyle, simple techniques]
-
A.
foodPreparationStyle
chosen
Indicates the manner or method by which food is prepared, cooked, or processed.
-
B.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
C.
cuisine
Indicates the type or style of food traditionally associated with or served by an entity (such as a restaurant or region).
-
D.
seasoningStyle
Indicates the characteristic way in which an item is flavored or seasoned, such as the method, intensity, or cultural style of its seasoning.
-
E.
cuisineSubtype
Indicates that one cuisine is a more specific subtype or variant within the broader category of another cuisine.
- 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_69c6888d8e3c81909db79714903baf31 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebda7b748190a230a22ecea79342 |
completed | March 27, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69c6e7705f4881909793071dee50c557 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:01 p.m.