Triple
T33704249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filet mignon |
E863540
|
entity |
| Predicate | marblingLevel |
P91025
|
FINISHED |
| Object | relatively low |
—
|
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: relatively low | Statement: [Filet mignon, marblingLevel, relatively low]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marblingLevel Context triple: [Filet mignon, marblingLevel, relatively low]
-
A.
marblingGrade
chosen
Indicates the quality level of intramuscular fat distribution (marbling) associated with a meat product.
-
B.
colorGrade
Indicates the qualitative or categorical assessment of an entity’s color according to a defined grading scale.
-
C.
meatQuality
Indicates the assessed level or characteristics of quality associated with a given piece or type of meat.
-
D.
hallmarkStrength
Indicates that something possesses a defining or characteristic strength that serves as a key feature or distinguishing quality.
-
E.
marbleType
Indicates that one entity is of a specific type or category of marble in relation to another entity.
- 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_69f3498844608190bb8f9b14908d2510 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fab27a108190a51a1c5713b98884 |
completed | May 3, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69f6f96dd4c8819093d6a7bd046a9ad5 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:43 a.m.