Triple
T38102209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Mountain Brewery |
E951412
|
entity |
| Predicate | hasBrewpub |
P77072
|
FINISHED |
| Object | Blue Mountain Brewery brewpub |
—
|
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: Blue Mountain Brewery brewpub | Statement: [Blue Mountain Brewery, hasBrewpub, Blue Mountain Brewery brewpub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrewpub Context triple: [Blue Mountain Brewery, hasBrewpub, Blue Mountain Brewery brewpub]
-
A.
hasBreweryFocus
Indicates that an entity (such as a business, product, or activity) is primarily oriented around, specialized in, or dedicated to breweries or brewing-related operations.
-
B.
hasIntegratedMicrobrewery
Indicates that an entity includes or contains a microbrewery as a built-in or internal component.
-
C.
hasBreweryOrFacility
chosen
Indicates that an entity possesses, operates, or is associated with a brewery or brewing-related facility.
-
D.
hasMajorBrewery
Indicates that a location or entity possesses or hosts a large, commercially significant brewery.
-
E.
hasBreweryScene
Indicates that a scene or event takes place in, or prominently features, a brewery.
- 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_69f76f04960c8190a83f14ae4c67f5bc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: May 3, 2026, 4:21 p.m.