Triple
T22441230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | water-boiled beef |
E554758
|
entity |
| Predicate | isTypicallyEatenWith |
P148210
|
FINISHED |
| Object | steamed rice |
—
|
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: steamed rice | Statement: [water-boiled beef, isTypicallyEatenWith, steamed rice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTypicallyEatenWith Context triple: [water-boiled beef, isTypicallyEatenWith, steamed rice]
-
A.
isOftenEaten
Indicates that the subject is frequently consumed as food by some agent or group.
-
B.
typicallyEatenAt
Indicates that something is most commonly or customarily eaten during a particular time, event, or context.
-
C.
isTypicallyConsumedFrom
Indicates that one entity is most commonly eaten or drunk using, contained in, or taken from the other entity.
-
D.
isTypicallyServedFor
Indicates that one item is most commonly or customarily served as a meal or course for the other (e.g., a dish typically served for breakfast, lunch, or dinner).
-
E.
isEatenIn
Indicates that one entity (typically food) is consumed within the context, location, or occasion specified by 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae1f82881908a611f134eb03f3d |
completed | April 29, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
| PDg | Predicate description generation | batch_69e8aa39e3388190b659d59948ebf3e6 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:47 p.m.