Triple
T8906233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hotto Motto |
E212065
|
entity |
| Predicate | foodSafetyPractice |
P86304
|
FINISHED |
| Object | cook-to-order preparation |
—
|
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: cook-to-order preparation | Statement: [Hotto Motto, foodSafetyPractice, cook-to-order preparation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foodSafetyPractice Context triple: [Hotto Motto, foodSafetyPractice, cook-to-order preparation]
-
A.
culinaryUse
Indicates that one entity is used in the preparation, flavoring, or serving of food or drink for another entity.
-
B.
animalWelfarePractice
Indicates practices, actions, or policies that affect the well-being, treatment, and living conditions of animals.
-
C.
mainFoodAffected
Indicates that a primary or central food item is directly impacted or influenced by a specified action or condition.
-
D.
administrationWithFood
Indicates that a substance (such as a medication) is to be taken together with food or during a meal.
-
E.
householdPractice
Indicates a relationship where an entity engages in or carries out a particular practice, behavior, or routine within the context of a household.
- F. None of above. chosen
Provenance (4 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_69ca839255248190b43984294abd92ae |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc64c51d6c819098dc33a480dfd462 |
completed | April 1, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69cc5ecf55248190a29f00fbf99f13c4 |
completed | March 31, 2026, 11:54 p.m. |
| PDg | Predicate description generation | batch_69cc604965c48190bbb6db0ae8108e67 |
completed | April 1, 2026, 12:01 a.m. |
Created at: March 30, 2026, 6:55 p.m.