Triple
T24726547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chipotle Rewards |
E618168
|
entity |
| Predicate | enrollmentChannel |
P125781
|
FINISHED |
| Object | in-restaurant sign-up |
—
|
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: in-restaurant sign-up | Statement: [Chipotle Rewards, enrollmentChannel, in-restaurant sign-up]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enrollmentChannel Context triple: [Chipotle Rewards, enrollmentChannel, in-restaurant sign-up]
-
A.
enrollment
Indicates the formal act of registering or being registered in a course, program, or institution, establishing an official participant–provider relationship.
-
B.
enrollmentModel
Indicates the type or structure of the enrollment relationship that governs how entities (such as users or participants) are registered or associated with a program, course, or service.
-
C.
registrationChannel
chosen
Indicates the method or medium through which a registration was initiated or completed between entities.
-
D.
enrolledIn
Indicates that one entity is formally registered as a participant in a course, program, or institution represented by another entity.
-
E.
enrollmentType
Indicates the specific category or mode under which an entity is enrolled in a program, service, or system.
- 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_69e2fab772608190b74163751047ff50 |
completed | April 18, 2026, 3:29 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442a977b08190b44eac040cb90211 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 3:59 a.m.