Triple
T2054691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norway Pavilion |
E45646
|
entity |
| Predicate | offersCuisine |
P35619
|
FINISHED |
| Object | Norwegian cuisine |
—
|
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: Norwegian cuisine | Statement: [Norway Pavilion, offersCuisine, Norwegian cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersCuisine Context triple: [Norway Pavilion, offersCuisine, Norwegian cuisine]
-
A.
offersMeal
Indicates that one entity provides or makes available a meal to another entity.
-
B.
offersServiceType
Indicates that one entity provides or makes available a specific type or category of service to another entity or the public.
-
C.
offersFeature
Indicates that one entity provides or makes available a particular feature or capability to another entity.
-
D.
dietaryOptions
Indicates the types of diets or food-related preferences, restrictions, or choices that are applicable to or offered for an entity.
-
E.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
- F. None of above. chosen
Provenance (4 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_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9a8518081909ba95a8ef9321f12 |
completed | March 7, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_69abb7abba508190b872f345d3ba51bb |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb94ec400819097596732aabed854 |
completed | March 7, 2026, 5:36 a.m. |
Created at: March 4, 2026, 7:40 p.m.