Triple
T19592561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Café am Neuen See |
E470271
|
entity |
| Predicate | indoorAreaType |
P70315
|
FINISHED |
| Object | restaurant hall |
—
|
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: restaurant hall | Statement: [Café am Neuen See, indoorAreaType, restaurant hall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: indoorAreaType Context triple: [Café am Neuen See, indoorAreaType, restaurant hall]
-
A.
hasIndoorArea
Indicates that an entity possesses or includes an area or space that is located indoors or within a building.
-
B.
hasIndoorType
Indicates that an entity is associated with a specific type or category of indoor environment or indoor feature.
-
C.
indoorOrOutdoor
Indicates whether an activity, event, or entity occurs inside a building (indoors) or outside in open air (outdoors).
-
D.
typeOfBuildingSpace
chosen
Indicates the specific kind or category of building space that an entity represents or occupies.
-
E.
spaceType
Indicates the category or kind of physical or conceptual space associated with an 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64057460c8190962e2e58f06b3985 |
completed | April 20, 2026, 3:03 p.m. |
| PD | Predicate disambiguation | batch_69e514dbdb988190b55931a8138c73e7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:43 p.m.