Triple
T10978620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yonezawa beef |
E259437
|
entity |
| Predicate | fatDistribution |
P96427
|
FINISHED |
| Object | fine marbling |
—
|
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: fine marbling | Statement: [Yonezawa beef, fatDistribution, fine marbling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fatDistribution Context triple: [Yonezawa beef, fatDistribution, fine marbling]
-
A.
fatStorage
Indicates the process or state in which an organism or system accumulates and retains fat as an energy reserve.
-
B.
fatColor
Indicates the color characteristic associated with an entity’s fat or fatty tissue.
-
C.
typicalFatContent
Indicates the usual or characteristic amount of fat contained in something, such as a food or product.
-
D.
typicalFatUsed
Indicates that a particular type of fat is commonly or characteristically used in a given context or application.
-
E.
primaryBodyType
Indicates the main physical form or category that characterizes an entity’s overall body structure or composition.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d771f7b874819087bf5a858905279b |
completed | April 9, 2026, 9:31 a.m. |
| PD | Predicate disambiguation | batch_69d72e9055908190b438f039574aaaaf |
completed | April 9, 2026, 4:44 a.m. |
| PDg | Predicate description generation | batch_69d732242fdc8190be77d1f730a42935 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:24 p.m.