Triple
T9513743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Olmsted |
E229467
|
entity |
| Predicate | hasRetailCharacteristic |
P88487
|
FINISHED |
| Object | regional shopping destinations |
—
|
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: regional shopping destinations | Statement: [North Olmsted, hasRetailCharacteristic, regional shopping destinations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetailCharacteristic Context triple: [North Olmsted, hasRetailCharacteristic, regional shopping destinations]
-
A.
hasRetailOption
Indicates that one entity offers, includes, or is associated with a particular retail option (such as a sales channel, purchase method, or retail configuration) for another entity.
-
B.
hasRetailCategory
Indicates that an entity is associated with a specific retail category or type of retail business.
-
C.
hasRetailProduct
Indicates that an entity offers, sells, or makes available a particular product in a retail context.
-
D.
hasRetailFormat
Indicates that one entity operates or is organized according to a particular retail format or store type.
-
E.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
- 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_69ca84777560819084cddd999badc1aa |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd986bfcac8190aa97f8975cb17f6c |
completed | April 1, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69cca567ca448190bf4bcce8ce7dd54f |
completed | April 1, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69cca89d0f0c8190b4528990fe708fca |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 7:58 p.m.