Triple
T25477744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russet Burbank potato |
E638477
|
entity |
| Predicate | cookingQuality |
P32634
|
FINISHED |
| Object | mealy texture when baked |
—
|
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: mealy texture when baked | Statement: [Russet Burbank potato, cookingQuality, mealy texture when baked]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cookingQuality Context triple: [Russet Burbank potato, cookingQuality, mealy texture when baked]
-
A.
hasCookingQuality
chosen
Indicates that something possesses a particular characteristic or attribute related to cooking, such as flavor, texture, or suitability for a cooking method.
-
B.
meatQuality
Indicates the assessed level or characteristics of quality associated with a given piece or type of meat.
-
C.
culinaryStatus
Indicates the current state or condition of something in relation to cooking or food preparation (e.g., raw, cooked, undercooked, burnt).
-
D.
meltingQuality
Indicates the degree or manner in which something melts, such as how easily, quickly, or smoothly it transitions from solid to liquid.
-
E.
culinaryUse
Indicates that one entity is used in the preparation, flavoring, or serving of food or drink for 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_69e75db9b964819096802dcf502e577e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f772a0248190a52aef4495a5b0a3 |
completed | May 2, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69f480789be08190ab252a6de3797200 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 2:26 p.m.