Triple
T5137239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas-style barbecue |
E115855
|
entity |
| Predicate | seasoningStyle |
P62832
|
FINISHED |
| Object | simple dry rub |
—
|
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: simple dry rub | Statement: [Texas-style barbecue, seasoningStyle, simple dry rub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seasoningStyle Context triple: [Texas-style barbecue, seasoningStyle, simple dry rub]
-
A.
isTypicallyGarnishedWith
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
B.
sauceType
Indicates the specific kind or category of sauce associated with an item or dish.
-
C.
servingStyle
Indicates how something (typically food or drink) is presented or offered for consumption or use.
-
D.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
E.
hasSpiciness
Indicates that one entity possesses a certain level or quality of spiciness in relation to another entity or a defined scale.
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7fef2e8c8190982dd67f50295ada |
completed | March 20, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69bd77ac2fc48190abeebb003a82384c |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd7fee42748190967013828973cce0 |
completed | March 20, 2026, 5:12 p.m. |
Created at: March 20, 2026, 1:43 p.m.