Triple
T11655711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Windows Certificate Store |
E277007
|
entity |
| Predicate | hasStoreLocation |
P100211
|
FINISHED |
| Object | LocalMachine |
—
|
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: LocalMachine | Statement: [Windows Certificate Store, hasStoreLocation, LocalMachine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStoreLocation Context triple: [Windows Certificate Store, hasStoreLocation, LocalMachine]
-
A.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
-
B.
hasNotableStore
Indicates that an entity operates or is associated with a store that is considered notable or significant in some way.
-
C.
hasOutletStores
Indicates that an entity operates or is associated with one or more outlet retail stores.
-
D.
flagshipStoreLocation
Indicates the location where an organization’s primary or most prominent store is situated.
-
E.
hasRetailStores
Indicates that an entity operates or possesses one or more physical retail store locations.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a3cee010819089cffdbefe5a6efb |
completed | April 10, 2026, 7:16 a.m. |
| PD | Predicate disambiguation | batch_69d85ddc780481909a3bc63832fe2bd2 |
completed | April 10, 2026, 2:18 a.m. |
| PDg | Predicate description generation | batch_69d87f30642c8190ad94fa061cde186b |
completed | April 10, 2026, 4:40 a.m. |
Created at: April 8, 2026, 9:39 p.m.