Triple
T30583329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | laphet thoke |
E778439
|
entity |
| Predicate | isUsuallyEatenWith |
P148210
|
FINISHED |
| Object | 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: rice | Statement: [laphet thoke, isUsuallyEatenWith, rice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUsuallyEatenWith Context triple: [laphet thoke, isUsuallyEatenWith, rice]
-
A.
isTypicallyEatenWith
chosen
Indicates that one item is commonly consumed together with another as part of the same eating occasion or dish.
-
B.
isTypicallyGarnishedWith
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
C.
servedTogetherWith
Indicates that two entities were provided, offered, or used at the same time as part of the same service, event, or context.
-
D.
isOftenEaten
Indicates that the subject is frequently consumed as food by some agent or group.
-
E.
isUsuallyCookedIn
Indicates that something is most commonly or typically prepared or cooked within a particular container, appliance, or environment.
- F. None of above.
Provenance (3 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_69f224a04b248190b0ca443ec86207b8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68945093481909c6eba86bc50870e |
completed | May 2, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:23 p.m.