Triple
T18632899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAS Royal Hotel, Copenhagen |
E455465
|
entity |
| Predicate | room606Status |
P132473
|
FINISHED |
| Object | preserved in original Arne Jacobsen design |
—
|
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: preserved in original Arne Jacobsen design | Statement: [SAS Royal Hotel, Copenhagen, room606Status, preserved in original Arne Jacobsen design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: room606Status Context triple: [SAS Royal Hotel, Copenhagen, room606Status, preserved in original Arne Jacobsen design]
-
A.
amberRoomStatus
Indicates the current condition or state of the Amber Room in relation to its existence, location, or preservation.
-
B.
chamberStatus
Indicates the current operational or physical condition of a chamber within a system or process.
-
C.
hasRoom
Indicates that an entity possesses, contains, or is associated with a specific room.
-
D.
reservationStatus
Indicates the current state or condition of a reservation within its lifecycle (e.g., pending, confirmed, canceled, completed).
-
E.
statusInHouse
Indicates the specific role, position, or standing an entity holds within a particular house or household.
- 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54fc5c7ec8190ab0c64f009583f96 |
completed | April 19, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69e478d4a7948190a4bb9223bb5dddfc |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e485f5d1588190b44f31cbc54c0a9d |
completed | April 19, 2026, 7:36 a.m. |
Created at: April 10, 2026, 11:46 a.m.