Triple
T4045400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuremberg bratwurst |
E84052
|
entity |
| Predicate | meatTexture |
P25911
|
FINISHED |
| Object | finely ground |
—
|
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: finely ground | Statement: [Nuremberg bratwurst, meatTexture, finely ground]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meatTexture Context triple: [Nuremberg bratwurst, meatTexture, finely ground]
-
A.
fleshTexture
chosen
Indicates the tactile quality or surface feel of an entity’s flesh, such as how smooth, firm, soft, or coarse it is.
-
B.
meatType
Indicates the specific category or kind of meat associated with an entity.
-
C.
typicalMeat
Indicates that something is commonly or characteristically used or regarded as meat in a given context.
-
D.
meatQuality
Indicates the assessed level or characteristics of quality associated with a given piece or type of meat.
-
E.
meatPreparation
Indicates the method or process by which meat is treated, cooked, or otherwise prepared for consumption.
- 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_69aed930bd5c819083e7dcc14fc44f69 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb5f85d48190ba80a0a24fbe438a |
completed | March 9, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69aef900386481909d04555a9ec9b0e3 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.