Triple
T14789104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montepulciano d'Abruzzo |
E347604
|
entity |
| Predicate | primaryFoodPairing |
P14740
|
FINISHED |
| Object | pasta with tomato sauce |
—
|
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: pasta with tomato sauce | Statement: [Montepulciano d'Abruzzo, primaryFoodPairing, pasta with tomato sauce]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryFoodPairing Context triple: [Montepulciano d'Abruzzo, primaryFoodPairing, pasta with tomato sauce]
-
A.
typicalFoodPairing
chosen
Indicates that one food item is commonly served, consumed, or matched together with another as a customary or complementary pairing.
-
B.
foodInteraction
Indicates an interaction or relationship involving food between entities, such as consumption, sharing, preparation, or exchange.
-
C.
favoriteFood
Indicates that one entity has a preferred or most liked food item in relation to another entity or context.
-
D.
intendedFood
Indicates that one entity is the food item that another entity plans or is meant to eat or consume.
-
E.
primaryFood
Indicates that one entity serves as the main or most important food source 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decaa1e9ec81908d7c26c1c4e43014 |
completed | April 14, 2026, 11:15 p.m. |
| PD | Predicate disambiguation | batch_69de8c090d1081909b5a9bf437499d6c |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:31 a.m.