Triple
T19251330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wagons-Lits restaurant cars |
E481398
|
entity |
| Predicate | cateringStandard |
P9631
|
FINISHED |
| Object | hotel-style cuisine on rails |
—
|
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: hotel-style cuisine on rails | Statement: [Wagons-Lits restaurant cars, cateringStandard, hotel-style cuisine on rails]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cateringStandard Context triple: [Wagons-Lits restaurant cars, cateringStandard, hotel-style cuisine on rails]
-
A.
cateringIncludes
Indicates that a catering service or arrangement encompasses or provides the specified item, service, or component as part of its offering.
-
B.
diningStyle
chosen
Indicates the manner or format in which dining is conducted, such as casual, formal, buffet, or family-style.
-
C.
servingStyle
Indicates how something (typically food or drink) is presented or offered for consumption or use.
-
D.
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).
-
E.
commonMealType
Indicates that two entities share the same general category or type of meal (e.g., breakfast, lunch, dinner).
- 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb30bf6c819094c44aceb544a023 |
completed | April 20, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69e4dd002d00819088b625056edfb74e |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:27 p.m.