Triple
T20380625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karato Market |
E497814
|
entity |
| Predicate | bestKnownDish |
P79219
|
FINISHED |
| Object | fugu sashimi |
—
|
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: fugu sashimi | Statement: [Karato Market, bestKnownDish, fugu sashimi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestKnownDish Context triple: [Karato Market, bestKnownDish, fugu sashimi]
-
A.
knownForDish
chosen
Indicates that an entity is recognized or notable for preparing, serving, or being associated with a particular dish.
-
B.
isNationalDishOf
Indicates that a particular food is officially or culturally recognized as the national dish of a specific country or region.
-
C.
traditionalDish
Indicates that the object is a dish customarily prepared, eaten, or recognized within the subject’s cultural or regional tradition.
-
D.
favoriteFood
Indicates that one entity has a preferred or most liked food item in relation to another entity or context.
-
E.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
- 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_69e0b4a5b7908190a972e4e7e698ae94 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678b026e081909541e545886c8380 |
completed | April 20, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:27 a.m.