Triple
T20174986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Binion's Gambling Hall and Hotel |
E492065
|
entity |
| Predicate | hotelStatus |
P138973
|
FINISHED |
| Object | former hotel |
—
|
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: former hotel | Statement: [Binion's Gambling Hall and Hotel, hotelStatus, former hotel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hotelStatus Context triple: [Binion's Gambling Hall and Hotel, hotelStatus, former hotel]
-
A.
reservationStatus
Indicates the current state or condition of a reservation within its lifecycle (e.g., pending, confirmed, canceled, completed).
-
B.
amberRoomStatus
Indicates the current condition or state of the Amber Room in relation to its existence, location, or preservation.
-
C.
hotelUsedFor
Indicates that something (such as a building, facility, or space) functions as or is utilized as a hotel.
-
D.
hotelClass
Indicates the classification or rating level assigned to a hotel, such as its star category or quality tier.
-
E.
keeperAccommodationStatus
Indicates the current type or condition of accommodation provided to or used by the keeper in relation to the relevant entity or context.
- 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.