Triple
T33751075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ginjinha |
E864842
|
entity |
| Predicate | isTypicallyConsumedAfter |
P177831
|
FINISHED |
| Object | meals |
—
|
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: meals | Statement: [Ginjinha, isTypicallyConsumedAfter, meals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTypicallyConsumedAfter Context triple: [Ginjinha, isTypicallyConsumedAfter, meals]
-
A.
isTypicallyConsumedFrom
Indicates that one entity is most commonly eaten or drunk using, contained in, or taken from the other entity.
-
B.
isTypicallyEatenWith
Indicates that one item is commonly consumed together with another as part of the same eating occasion or dish.
-
C.
commonlyConsumedAt
Indicates that one entity is typically eaten or drunk during, or in association with, a particular time, event, or context.
-
D.
consumedAfter
Indicates that one item is consumed only after another specified item has been consumed.
-
E.
isEatenFor
Indicates that one entity is consumed as food for the benefit, nourishment, or use of 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_69f3498c35f881909df279ae4270f831 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7051ad6e4819095e82bbd64761803 |
completed | May 3, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69f700fe24e08190998e2c96fbaaad38 |
completed | May 3, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69f70519f114819080659840c04d7911 |
completed | May 3, 2026, 8:19 a.m. |
Created at: May 1, 2026, 1:45 a.m.