Triple
T23528635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tapestry Collection by Hilton |
E576500
|
entity |
| Predicate | roomTypeRange |
P153123
|
FINISHED |
| Object | standard rooms |
—
|
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: standard rooms | Statement: [Tapestry Collection by Hilton, roomTypeRange, standard rooms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roomTypeRange Context triple: [Tapestry Collection by Hilton, roomTypeRange, standard rooms]
-
A.
hotelFloorRange
Indicates the range of floors within a hotel on which something (such as a room, facility, or service) is located or available.
-
B.
numberOfBedrooms
Indicates the quantity of bedrooms associated with a given property or dwelling.
-
C.
bedCount
Indicates the number of beds associated with an entity, such as a room, facility, or accommodation.
-
D.
hasSingleRooms
Indicates that an entity offers or includes individual rooms intended for single occupancy.
-
E.
numberOfHotelRooms
Indicates the total count of rooms that a given hotel has.
- 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_69e245f5a8848190a2ba42e271c6c31f |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ac758038819098f5f597be39274e |
completed | April 29, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
| PDg | Predicate description generation | batch_69f12760784c8190aaeff002ef31febe |
completed | April 28, 2026, 9:32 p.m. |
Created at: April 17, 2026, 6:09 p.m.