Triple
T6767367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chipotle Mexican Grill |
E154755
|
entity |
| Predicate | hasIngredientCategory |
P40800
|
FINISHED |
| Object | non-GMO ingredients |
—
|
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: non-GMO ingredients | Statement: [Chipotle Mexican Grill, hasIngredientCategory, non-GMO ingredients]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIngredientCategory Context triple: [Chipotle Mexican Grill, hasIngredientCategory, non-GMO ingredients]
-
A.
hasMainIngredient
Indicates that one entity is the primary or most significant ingredient used to make another entity.
-
B.
usesIngredient
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
C.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
-
D.
ingredientType
chosen
Indicates that one entity is classified as a specific type or category of ingredient in relation to another.
-
E.
haveCuisine
Indicates that an entity (such as a restaurant or place) offers, serves, or is associated with a particular type or style of 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_69c688109c1c8190added9a221292af0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d231b79c81908a4f7fa8f253706d |
completed | March 27, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:12 p.m.