Triple
T25074543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snezhanka salad |
E628010
|
entity |
| Predicate | canBeServedWith |
P148210
|
FINISHED |
| Object | bread |
—
|
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: bread | Statement: [Snezhanka salad, canBeServedWith, bread]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeServedWith Context triple: [Snezhanka salad, canBeServedWith, bread]
-
A.
servesWith
Indicates that one entity is customarily presented, used, or consumed together with another as a complementary accompaniment.
-
B.
servedTogetherWith
Indicates that two entities were provided, offered, or used at the same time as part of the same service, event, or context.
-
C.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
-
D.
isTypicallyEatenWith
chosen
Indicates that one item is commonly consumed together with another as part of the same eating occasion or dish.
-
E.
servesProduct
Indicates that one entity provides or offers a particular product to others, typically in a commercial or service context.
- 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_69e2ff2d71dc8190b4758e57d643cbe4 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f5ffc74fa481909b4fe24a9337f9eb |
completed | May 2, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7f99dc08190afcfb3bc4dfbec1d |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 18, 2026, 6:20 a.m.