Triple
T17077493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Costa Club |
E414387
|
entity |
| Predicate | registrationChannel |
P125781
|
FINISHED |
| Object | Costa Coffee mobile app |
—
|
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: Costa Coffee mobile app | Statement: [Costa Club, registrationChannel, Costa Coffee mobile app]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: registrationChannel Context triple: [Costa Club, registrationChannel, Costa Coffee mobile app]
-
A.
registrationContext
Indicates the situational or environmental context under which a registration event occurs, such as conditions, purpose, or setting.
-
B.
registrationFor
Indicates a relationship where one entity is enrolled, signed up, or formally recorded to participate in, use, or be associated with another entity (such as an event, service, or program).
-
C.
register
Indicates that an entity formally records or enrolls another entity or itself in an official system, list, or record.
-
D.
registrationCategory
Indicates the classification or type under which an entity is formally registered within a system or registry.
-
E.
registrationExample
Indicates that an instance serves as an illustrative or sample case of a particular registration.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbc625c48190b679a521180e10ad |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:34 a.m.