Triple
T11659991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodland Mansion |
E277096
|
entity |
| Predicate | containsRoomType |
P5521
|
FINISHED |
| Object | Bedroom |
—
|
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: Bedroom | Statement: [Woodland Mansion, containsRoomType, Bedroom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsRoomType Context triple: [Woodland Mansion, containsRoomType, Bedroom]
-
A.
hasHotelType
Indicates that a hotel is classified as belonging to a specific type or category (e.g., resort, boutique, hostel).
-
B.
hasRoom
chosen
Indicates that an entity possesses, contains, or is associated with a specific room.
-
C.
hasReservationType
Indicates that an entity is associated with a specific category or type of reservation.
-
D.
hasResortType
Indicates that an entity (such as a resort or accommodation) is associated with a specific category or type of resort (e.g., beach resort, ski resort, spa resort).
-
E.
hasReadingRoomType
Indicates that an entity (such as a facility or building) has a specific type or category of reading room.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a3d19c788190826d849a6ffedc72 |
completed | April 10, 2026, 7:16 a.m. |
| PD | Predicate disambiguation | batch_69d88a73f9ac819095662042804bf40a |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:39 p.m.