Triple
T30864417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Shield Stamps showrooms |
E786156
|
entity |
| Predicate | hadSystem |
P170575
|
FINISHED |
| Object | catalogue-based redemption |
—
|
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: catalogue-based redemption | Statement: [Green Shield Stamps showrooms, hadSystem, catalogue-based redemption]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadSystem Context triple: [Green Shield Stamps showrooms, hadSystem, catalogue-based redemption]
-
A.
hadModel
Indicates that an entity possessed, used, or was associated with a particular model (e.g., a product, design, or version) at some point in time.
-
B.
hadBase
Indicates that an entity maintained or operated from a particular base location or primary site.
-
C.
hadOrgan
Indicates that an entity previously possessed or contained a specific organ as part of its body.
-
D.
hadNo
Indicates that one entity completely lacked or did not possess another entity, attribute, or relationship.
-
E.
hadFort
Indicates that an entity possessed, controlled, or contained a fort at some time.
- 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_69f224b9df2c819086f55f8bcf7f382e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f691ab31288190afe04c1a55477a9f |
completed | May 3, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_69f68fb914b88190b0cad83ea9fe9dfc |
completed | May 2, 2026, 11:58 p.m. |
Created at: April 29, 2026, 8:47 p.m.