Triple
T7416372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaga Onsen |
E171139
|
entity |
| Predicate | typicalBathType |
P76823
|
FINISHED |
| Object | indoor onsen baths |
—
|
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: indoor onsen baths | Statement: [Kaga Onsen, typicalBathType, indoor onsen baths]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBathType Context triple: [Kaga Onsen, typicalBathType, indoor onsen baths]
-
A.
showerType
Indicates the specific kind or category of shower associated with an entity (e.g., walk-in, bathtub-shower combo, outdoor shower).
-
B.
numberOfBathrooms
Indicates the total count of bathrooms associated with an entity (such as a property or unit).
-
C.
hasBathhouse
Indicates that one entity possesses, contains, or is associated with a bathhouse facility.
-
D.
typicalUnitConfiguration
Indicates the standard or commonly used arrangement, composition, or setup of a unit in a given context.
-
E.
typicalUnitType
Indicates that one entity is the standard or commonly used unit type associated with measuring or expressing the other entity.
- 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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2c7ae0c8190a8348d6223aeeecc |
completed | March 27, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1c3307481909a7f6bb69d4fddac |
completed | March 27, 2026, 9:08 p.m. |
Created at: March 27, 2026, 3:11 p.m.