Triple
T18128233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aischgrund |
E433938
|
entity |
| Predicate | foodSpeciality |
P6863
|
FINISHED |
| Object | fried carp |
—
|
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: fried carp | Statement: [Aischgrund, foodSpeciality, fried carp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foodSpeciality Context triple: [Aischgrund, foodSpeciality, fried carp]
-
A.
foodCulture
Indicates the relationship between a place or group and its characteristic traditions, practices, and preferences surrounding food and eating.
-
B.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
-
C.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
D.
cuisine
chosen
Indicates the type or style of food traditionally associated with or served by an entity (such as a restaurant or region).
-
E.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
- 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddf061b48190b67356f1c266b80a |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:29 a.m.