Triple
T20174987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Binion's Gambling Hall and Hotel |
E492065
|
entity |
| Predicate | hotelRoomsStatus |
P138974
|
FINISHED |
| Object | closed |
—
|
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: closed | Statement: [Binion's Gambling Hall and Hotel, hotelRoomsStatus, closed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hotelRoomsStatus Context triple: [Binion's Gambling Hall and Hotel, hotelRoomsStatus, closed]
-
A.
amberRoomStatus
Indicates the current condition or state of the Amber Room in relation to its existence, location, or preservation.
-
B.
room606Status
Indicates the current condition or occupancy state associated with room 606.
-
C.
numberOfHotelRooms
Indicates the total count of rooms that a given hotel has.
-
D.
hasRoom
Indicates that an entity possesses, contains, or is associated with a specific room.
-
E.
hasRetiringRooms
Indicates that an entity provides or is associated with retiring rooms, such as private rest or waiting areas for temporary use.
- 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e668eaa3b88190bef4f2db0125fdfc |
completed | April 20, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56700b1a08190ace53cf95827d72d |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:36 p.m.