Triple
T38560813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Listeria |
E928071
|
entity |
| Predicate | foodAssociation |
P145531
|
FINISHED |
| Object | ready-to-eat meats |
—
|
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: ready-to-eat meats | Statement: [Listeria, foodAssociation, ready-to-eat meats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foodAssociation Context triple: [Listeria, foodAssociation, ready-to-eat meats]
-
A.
foodInteraction
Indicates an interaction or relationship involving food between entities, such as consumption, sharing, preparation, or exchange.
-
B.
typicalFoodPairing
Indicates that one food item is commonly served, consumed, or matched together with another as a customary or complementary pairing.
-
C.
foodRelatedMotif
Indicates a recurring theme, symbol, or pattern in which food plays a central role in the relationship or action between entities.
-
D.
ingredientType
Indicates that one entity is classified as a specific type or category of ingredient in relation to another.
-
E.
relationshipToFood
chosen
Indicates the type of connection or association an entity has with food, such as consumption, production, preference, or other food-related roles.
- 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_69f76eb8d1808190a588af29d8b266d6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.