Triple
T9301308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hilton Tower |
E223766
|
entity |
| Predicate | hotelFloors |
P26383
|
FINISHED |
| Object | lower and middle floors |
—
|
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: lower and middle floors | Statement: [Hilton Tower, hotelFloors, lower and middle floors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hotelFloors Context triple: [Hilton Tower, hotelFloors, lower and middle floors]
-
A.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
B.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
C.
hotelFloorRange
chosen
Indicates the range of floors within a hotel on which something (such as a room, facility, or service) is located or available.
-
D.
hasOfficeFloors
Indicates that one entity (typically a building or structure) contains floors that are designated or used as office space.
-
E.
numberOfFloorsServed
Indicates the total count of distinct floors that are served or accessed by a given entity (such as an elevator or service system).
- 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_69ca8423edb08190bc0c91287a484768 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd08d1d954819098be177addafa406 |
completed | April 1, 2026, noon |
| PD | Predicate disambiguation | batch_69cc7a5ef1908190bc5ca166bb895af6 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:36 p.m.