Triple
T5931932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lagunitas Brewing Company |
E131956
|
entity |
| Predicate | hasAlcoholLicenseType |
P19269
|
FINISHED |
| Object | brewpub and production brewery |
—
|
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: brewpub and production brewery | Statement: [Lagunitas Brewing Company, hasAlcoholLicenseType, brewpub and production brewery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlcoholLicenseType Context triple: [Lagunitas Brewing Company, hasAlcoholLicenseType, brewpub and production brewery]
-
A.
servesAlcohol
Indicates that an establishment or provider offers and supplies alcoholic beverages to customers or participants.
-
B.
hasLicense
Indicates that an entity possesses a valid authorization or permit, typically granted by an authority, to perform a specific activity or use something.
-
C.
drinkingPermitted
Indicates that consuming alcoholic beverages is allowed in a given context, location, or situation.
-
D.
alcoholType
Indicates the specific kind or category of alcohol associated with an entity (e.g., beer, wine, spirits).
-
E.
typeOfLicense
chosen
Indicates the specific kind or category of license associated with an entity.
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03f26f51881908cc253fe5775a1fc |
completed | March 22, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69c03355caf08190b960563a1aed23f9 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4 p.m.