Triple
T34187067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dinty Moore |
E876989
|
entity |
| Predicate | containsVegetables |
P202189
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Dinty Moore, containsVegetables, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsVegetables Context triple: [Dinty Moore, containsVegetables, yes]
-
A.
mainVegetable
Indicates that one vegetable is the primary or most important vegetable in a given dish, recipe, or context.
-
B.
canBeVegetarian
Indicates that an entity is capable of being classified or used as vegetarian, typically meaning it can be included in a vegetarian context or diet.
-
C.
containsNumberOfVegetableServingsPer8oz
Indicates the quantity of vegetable servings present in each 8-ounce portion of an item.
-
D.
isVegetarian
Indicates that an entity follows a vegetarian diet, avoiding the consumption of meat and possibly other animal products.
-
E.
canBeVegan
Indicates that the subject is capable of being prepared, consumed, or existing in a way that meets vegan requirements.
- 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_69f349ae640c8190b9cd220b5368d8b6 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a005e8a2f7c819085bfc6f04b866d87 |
completed | May 10, 2026, 10:31 a.m. |
| PD | Predicate disambiguation | batch_6a005de82ef08190a015b385d1d3443c |
completed | May 10, 2026, 10:28 a.m. |
| PDg | Predicate description generation | batch_6a005e89803c8190ad732ad15affb81f |
completed | May 10, 2026, 10:31 a.m. |
Created at: May 1, 2026, 1:55 a.m.