Triple
T26810554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bell, Kemsing |
E671978
|
entity |
| Predicate | servesTypeOfCuisine |
P48322
|
FINISHED |
| Object | pub food |
—
|
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: pub food | Statement: [The Bell, Kemsing, servesTypeOfCuisine, pub food]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesTypeOfCuisine Context triple: [The Bell, Kemsing, servesTypeOfCuisine, pub food]
-
A.
servesType
chosen
Indicates that one entity provides, offers, or is used to deliver a particular type, category, or kind of thing or service.
-
B.
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).
-
C.
isTypicallyServedIn
Indicates that something (such as a food or drink) is most commonly or customarily presented or contained within a particular type of vessel or container.
-
D.
typeOfAssemblyServed
Indicates the specific type or category of assembly that is being served or catered to by an entity or action.
-
E.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
- 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_69eeb3225a3c8190aaf6746efeded2f3 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
Created at: April 27, 2026, 4:29 a.m.