Triple
T4606710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landscape of Flavors |
E100453
|
entity |
| Predicate | menuCharacteristic |
P54721
|
FINISHED |
| Object | diverse dishes |
—
|
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: diverse dishes | Statement: [Landscape of Flavors, menuCharacteristic, diverse dishes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: menuCharacteristic Context triple: [Landscape of Flavors, menuCharacteristic, diverse dishes]
-
A.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
B.
fruitCharacteristic
Indicates that a specified characteristic or property is attributed to a particular fruit.
-
C.
featuresItem
chosen
Indicates that one entity includes, presents, or highlights another entity as a notable item or component.
-
D.
typicalFeatures
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
E.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
- 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_69bd43cce1e08190a07d53af6a9b6c24 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd599c50d08190ab226cd0691e29f9 |
completed | March 20, 2026, 2:28 p.m. |
| PD | Predicate disambiguation | batch_69bd522e2d5c8190937d0b5574f78f99 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:12 p.m.