Triple
T7835352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo DisneySea Hotel MiraCosta |
E181676
|
entity |
| Predicate | numberOfGuestRooms |
P2402
|
FINISHED |
| Object | approximately 500 |
—
|
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: approximately 500 | Statement: [Tokyo DisneySea Hotel MiraCosta, numberOfGuestRooms, approximately 500]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGuestRooms Context triple: [Tokyo DisneySea Hotel MiraCosta, numberOfGuestRooms, approximately 500]
-
A.
numberOfHotelRooms
chosen
Indicates the total count of rooms that a given hotel has.
-
B.
numberOfGuestRoomWings
Indicates the count of distinct guest room wings associated with a given property or facility.
-
C.
numberOfBedrooms
Indicates the quantity of bedrooms associated with a given property or dwelling.
-
D.
approximateNumberOfRooms
Indicates an estimated or not precisely known count of rooms associated with an entity.
-
E.
bedCount
Indicates the number of beds associated with an entity, such as a room, facility, or accommodation.
- 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_69ca8284a25c8190a1a20afad30da792 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb064b872081908e269f4fe1b85436 |
completed | March 30, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69cae91e98988190abd4ece75932c589 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:46 p.m.