Triple
T19059321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Six Bells Brewery |
E466483
|
entity |
| Predicate | hasBreweryFocus |
P134935
|
FINISHED |
| Object | cask-conditioned beer |
—
|
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: cask-conditioned beer | Statement: [Six Bells Brewery, hasBreweryFocus, cask-conditioned beer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBreweryFocus Context triple: [Six Bells Brewery, hasBreweryFocus, cask-conditioned beer]
-
A.
hasBreweryOrFacility
Indicates that an entity possesses, operates, or is associated with a brewery or brewing-related facility.
-
B.
hasMajorBrewery
Indicates that a location or entity possesses or hosts a large, commercially significant brewery.
-
C.
hasNearbyBrewery
Indicates that one entity is located close to or in the vicinity of a brewery.
-
D.
hasIntegratedMicrobrewery
Indicates that an entity includes or contains a microbrewery as a built-in or internal component.
-
E.
hasBreweryScene
Indicates that a scene or event takes place in, or prominently features, a brewery.
- 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5dc08572c8190af2f8bcfe9d1616c |
completed | April 20, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69e4b99633c8819097988608c278ecf8 |
completed | April 19, 2026, 11:16 a.m. |
| PDg | Predicate description generation | batch_69e4c0fc3c4c8190abbfe06e1bd3325c |
completed | April 19, 2026, 11:48 a.m. |
Created at: April 10, 2026, 12:03 p.m.