Triple
T20465316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emirates First Class Lounge |
E502032
|
entity |
| Predicate | offersFoodType |
P35619
|
FINISHED |
| Object | international 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: international cuisine | Statement: [Emirates First Class Lounge, offersFoodType, international cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersFoodType Context triple: [Emirates First Class Lounge, offersFoodType, international cuisine]
-
A.
offersCuisine
chosen
Indicates that one entity provides or serves a particular type or style of cuisine to others.
-
B.
offersFoodInLocation
Indicates that an entity provides or serves food at a specified location.
-
C.
offersFoodAndBeverage
Indicates that an entity provides both food and drink to another entity or for general consumption.
-
D.
offersMeal
Indicates that one entity provides or makes available a meal to another entity.
-
E.
servesType
Indicates that one entity provides, offers, or is used to deliver a particular type, category, or kind of thing or service.
- 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_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696a9489081908990c691a36ba04d |
completed | April 20, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:33 a.m.