Triple
T5609562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niigata Sake no Jin |
E147317
|
entity |
| Predicate | numberOfParticipatingBreweries |
P26114
|
FINISHED |
| Object | over 80 |
—
|
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: over 80 | Statement: [Niigata Sake no Jin, numberOfParticipatingBreweries, over 80]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfParticipatingBreweries Context triple: [Niigata Sake no Jin, numberOfParticipatingBreweries, over 80]
-
A.
numberOfBreweries
chosen
Indicates the count of breweries associated with a given entity or within a specified context.
-
B.
hasMajorBrewery
Indicates that a location or entity possesses or hosts a large, commercially significant brewery.
-
C.
hasIntegratedMicrobrewery
Indicates that an entity includes or contains a microbrewery as a built-in or internal component.
-
D.
hasBreweryScene
Indicates that a scene or event takes place in, or prominently features, a brewery.
-
E.
breweryType
Indicates the specific category or classification of a brewery based on its operational or business characteristics.
- 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_69c0090500f881908374285baf0ac46f |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020fe7ee0819088ced51afd9a4f93 |
completed | March 22, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69c01b1b3c98819080687d18ab10a914 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:39 p.m.