Triple
T20504170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tampa Cuban sandwich |
E503383
|
entity |
| Predicate | meatComponent |
P22120
|
FINISHED |
| Object | roast pork |
—
|
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: roast pork | Statement: [Tampa Cuban sandwich, meatComponent, roast pork]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meatComponent Context triple: [Tampa Cuban sandwich, meatComponent, roast pork]
-
A.
meatType
Indicates the specific category or kind of meat associated with an entity.
-
B.
typicalMeat
chosen
Indicates that something is commonly or characteristically used or regarded as meat in a given context.
-
C.
notableMeatProduct
Indicates that one entity is a meat-based product that is especially prominent, well-known, or significant in relation to the other entity.
-
D.
meatPreparation
Indicates the method or process by which meat is treated, cooked, or otherwise prepared for consumption.
-
E.
meatQuality
Indicates the assessed level or characteristics of quality associated with a given piece or type of meat.
- 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_69e0b4b1e52c8190894281cf7e3283ab |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69dc539908190a18918fd9b7a829d |
completed | April 20, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69e59fcdf6e08190a604204615dc56e6 |
completed | April 20, 2026, 3:38 a.m. |
Created at: April 16, 2026, 11:35 a.m.