Triple
T22593137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stilton cheese (production area) |
E565000
|
entity |
| Predicate | cheeseStyle |
P60147
|
FINISHED |
| Object | English blue cheese |
—
|
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: English blue cheese | Statement: [Stilton cheese (production area), cheeseStyle, English blue cheese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cheeseStyle Context triple: [Stilton cheese (production area), cheeseStyle, English blue cheese]
-
A.
cheeseType
chosen
Indicates that one entity is a specific type or variety of cheese in relation to another entity.
-
B.
cheeseSpeciality
Indicates that one entity is known for or specializes in producing or offering a particular type of cheese.
-
C.
traditionalCheese
Indicates that something is recognized as a cheese made according to established, customary, or historically rooted methods or styles.
-
D.
cheeseMadeFrom
Indicates that one entity is produced or derived as cheese from another entity (typically a source ingredient such as milk).
-
E.
cheeseRipeningStyle
Indicates the method or process by which a cheese is matured or aged to develop its flavor and texture.
- 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_69e245836014819091b91ed3074742a3 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f16163cb248190b377b110d80a6730 |
completed | April 29, 2026, 1:39 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 2:49 p.m.