Triple
T16788609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kankaiji Onsen district |
E408043
|
entity |
| Predicate | typicalAccommodationType |
P75185
|
FINISHED |
| Object | Japanese-style room |
—
|
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: Japanese-style room | Statement: [Kankaiji Onsen district, typicalAccommodationType, Japanese-style room]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAccommodationType Context triple: [Kankaiji Onsen district, typicalAccommodationType, Japanese-style room]
-
A.
accommodationStyle
chosen
Indicates the manner or type of lodging or housing arrangement provided or used in a given context.
-
B.
sleepingAccommodation
Indicates that one entity serves as a place or facility where another entity can sleep or stay overnight.
-
C.
hasHotelType
Indicates that a hotel is classified as belonging to a specific type or category (e.g., resort, boutique, hostel).
-
D.
passengerAccommodation
Indicates that an entity provides or is designated as seating, lodging, or space intended for use by passengers.
-
E.
hasAccommodation
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b21c49788190b9a2ca2101604f64 |
completed | April 18, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.