Triple
T12366950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meals, Ready-to-Eat |
E294897
|
entity |
| Predicate | dailyRationPlanning |
P104803
|
FINISHED |
| Object | three MREs per day per person |
—
|
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: three MREs per day per person | Statement: [Meals, Ready-to-Eat, dailyRationPlanning, three MREs per day per person]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dailyRationPlanning Context triple: [Meals, Ready-to-Eat, dailyRationPlanning, three MREs per day per person]
-
A.
foodRationingInHostCountry
Indicates that the host country imposes restrictions or controlled distribution on available food supplies.
-
B.
nutritionComponent
Indicates that one entity is a nutritional constituent, ingredient, or component of another (typically a food, diet, or nutritional product).
-
C.
administrativeDivisionToday
Indicates that one entity currently functions as an administrative subdivision or jurisdictional unit within the other.
-
D.
administrationWithFood
Indicates that a substance (such as a medication) is to be taken together with food or during a meal.
-
E.
foodSources
Indicates a relationship where one entity serves as a source of food or nourishment for another entity.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d9429ff2bc8190b09adf8f57fad451 |
completed | April 10, 2026, 6:34 p.m. |
Created at: April 8, 2026, 9:54 p.m.