Triple
T20504167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tampa Cuban sandwich |
E503383
|
entity |
| Predicate | distinguishingIngredient |
P12771
|
FINISHED |
| Object | Genoa salami |
—
|
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: Genoa salami | Statement: [Tampa Cuban sandwich, distinguishingIngredient, Genoa salami]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distinguishingIngredient Context triple: [Tampa Cuban sandwich, distinguishingIngredient, Genoa salami]
-
A.
ingredientType
Indicates that one entity is classified as a specific type or category of ingredient in relation to another.
-
B.
distinguishingTrait
Indicates that a particular characteristic or feature uniquely differentiates one entity from another.
-
C.
usesIngredient
chosen
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
D.
hasMainIngredient
Indicates that one entity is the primary or most significant ingredient used to make another entity.
-
E.
usesIngredientInfluenceFrom
Indicates that one entity incorporates or applies the influence, properties, or effects derived from a particular ingredient in its action or outcome.
- 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.