Triple
T72001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PlumpJack wine store |
E1440
|
entity |
| Predicate | hasRetailModel |
P1395
|
FINISHED |
| Object | brick-and-mortar store |
—
|
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: brick-and-mortar store | Statement: [PlumpJack wine store, hasRetailModel, brick-and-mortar store]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetailModel Context triple: [PlumpJack wine store, hasRetailModel, brick-and-mortar store]
-
A.
hasMarket
Indicates that an entity possesses, operates in, or is associated with a particular market or marketplace.
-
B.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
C.
availableAs
chosen
Indicates that one entity can be used, accessed, or offered in the form, role, or capacity of another entity.
-
D.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
E.
formerBrand
Indicates that an entity was previously used or recognized as a brand for another entity but is no longer its current brand.
- F. None of above.
Provenance (3 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f6997c081908b202f937eb2b14f |
completed | Feb. 28, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69a24eab7f408190a8275cb82474f575 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.