Triple
T11497528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Portugal |
E272575
|
entity |
| Predicate | hasTypicalCuisine |
P59511
|
FINISHED |
| Object | seafood 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: seafood dishes | Statement: [Southern Portugal, hasTypicalCuisine, seafood dishes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalCuisine Context triple: [Southern Portugal, hasTypicalCuisine, seafood dishes]
-
A.
haveCuisine
chosen
Indicates that an entity (such as a restaurant or place) offers, serves, or is associated with a particular type or style of cuisine.
-
B.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
C.
isTypicallyServedFor
Indicates that one item is most commonly or customarily served as a meal or course for the other (e.g., a dish typically served for breakfast, lunch, or dinner).
-
D.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
-
E.
hasCuisineRecognition
Indicates that an entity has received formal recognition, awards, or notable acknowledgment specifically for its 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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85de27db081909ccdb4ab0ef75bdb |
completed | April 10, 2026, 2:18 a.m. |
| PD | Predicate disambiguation | batch_69d808736c5c8190899b5b3b2e797f65 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:36 p.m.