Triple
T4483711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flammekueche |
E107184
|
entity |
| Predicate | typicalServingStyle |
P14779
|
FINISHED |
| Object | cut into rectangular slices |
—
|
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: cut into rectangular slices | Statement: [Flammekueche, typicalServingStyle, cut into rectangular slices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalServingStyle Context triple: [Flammekueche, typicalServingStyle, cut into rectangular slices]
-
A.
servingStyle
chosen
Indicates how something (typically food or drink) is presented or offered for consumption or use.
-
B.
diningStyle
Indicates the manner or format in which dining is conducted, such as casual, formal, buffet, or family-style.
-
C.
servesSide
Indicates that one entity is provided or presented as an accompanying side item to another primary entity.
-
D.
servesType
Indicates that one entity provides, offers, or is used to deliver a particular type, category, or kind of thing or service.
-
E.
typicallyServedAs
Indicates that something is most commonly presented, used, or offered in a particular role, form, or function.
- 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd556d29f08190bab1e872dd7e819f |
completed | March 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69bd5213e3d0819094b026989e686f01 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 12:58 p.m.