Triple
T36274730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wagyu beef |
E892772
|
entity |
| Predicate | hasHealthAspect |
P186802
|
FINISHED |
| Object | high monounsaturated fat content |
—
|
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: high monounsaturated fat content | Statement: [Wagyu beef, hasHealthAspect, high monounsaturated fat content]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHealthAspect Context triple: [Wagyu beef, hasHealthAspect, high monounsaturated fat content]
-
A.
healthAttribute
chosen
Indicates that one entity specifies or characterizes a particular health-related property, condition, or quality of another entity.
-
B.
hasHealthArea
Indicates that an entity is associated with, or falls within the scope of, a particular health-related domain or area of concern.
-
C.
healthType
Indicates the specific category or classification of health status or condition associated with an entity.
-
D.
hasHealthCareCharacteristic
Indicates that an entity possesses a specific healthcare-related attribute, quality, or feature.
-
E.
hasHealthConcern
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
- 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_69f76e488f34819083e254dbe288c27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fdbaa226708190b8ed96e93aad38de |
completed | May 8, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69fdb58b07e48190837e00966de050d4 |
completed | May 8, 2026, 10:06 a.m. |
Created at: May 3, 2026, 4:09 p.m.