Triple
T34312166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cooking for Two |
E880479
|
entity |
| Predicate | hasNumberOfServingsPerRecipe |
P197606
|
FINISHED |
| Object | two |
—
|
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: two | Statement: [Cooking for Two, hasNumberOfServingsPerRecipe, two]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfServingsPerRecipe Context triple: [Cooking for Two, hasNumberOfServingsPerRecipe, two]
-
A.
commonServingSize
Indicates that two or more food items share the same standard or typical serving size used for comparison or labeling.
-
B.
hasServingSizeVariant
Indicates that one item is a version of another that differs specifically in serving size.
-
C.
marketedAsServing
Indicates that something is promoted or advertised as providing service to a particular audience, purpose, or function.
-
D.
traditionallyServes
Indicates that one entity customarily or historically provides or presents another entity, especially in a cultural or culinary context.
-
E.
typicalPortionPerBowl
Indicates the usual or standard quantity served in a single bowl for a given item or context.
- 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_69f349b8bb6c8190ad12a7957a574f04 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe9dfaa2d08190b2084f63f842eb6b |
completed | May 9, 2026, 2:37 a.m. |
| PD | Predicate disambiguation | batch_69fe9bba947c81908b0b2b92a4d19b37 |
completed | May 9, 2026, 2:28 a.m. |
| PDg | Predicate description generation | batch_69fe9df9561c8190a068f91c9fc78e56 |
completed | May 9, 2026, 2:37 a.m. |
Created at: May 1, 2026, 1:57 a.m.