Triple
T17542468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morrisons supermarket site |
E427231
|
entity |
| Predicate | hasPointOfSaleSystem |
P127857
|
FINISHED |
| Object | electronic POS terminals |
—
|
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: electronic POS terminals | Statement: [Morrisons supermarket site, hasPointOfSaleSystem, electronic POS terminals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPointOfSaleSystem Context triple: [Morrisons supermarket site, hasPointOfSaleSystem, electronic POS terminals]
-
A.
hasRetailKiosks
Indicates that one entity operates or maintains retail kiosks associated with or located within another entity.
-
B.
hasPASystem
Indicates that an entity possesses or is equipped with a public address (PA) system.
-
C.
hasRevenueSystem
Indicates that one entity possesses, uses, or is associated with a particular revenue-generating system or mechanism.
-
D.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
-
E.
hasNotableStore
Indicates that an entity operates or is associated with a store that is considered notable or significant in some way.
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4545f1fa08190870c9244d06cf5f6 |
completed | April 19, 2026, 4:04 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fb39948190a82a597c5bac5c57 |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb37d148190b7f38599c06594ee |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:49 a.m.