Triple
T20046595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geihinkan Kokyō Akasaka Rikyu |
E497572
|
entity |
| Predicate | hasStateDiningRoom |
P138505
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Geihinkan Kokyō Akasaka Rikyu, hasStateDiningRoom, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStateDiningRoom Context triple: [Geihinkan Kokyō Akasaka Rikyu, hasStateDiningRoom, yes]
-
A.
hasDiningFeature
Indicates that something possesses a specific characteristic, amenity, or attribute related to dining.
-
B.
hasCharacterDining
Indicates that an entity offers or includes dining experiences where guests can eat while interacting with costumed characters.
-
C.
hasDiningFocus
Indicates that an entity is primarily oriented toward or specialized in dining-related activities, services, or experiences.
-
D.
hasDiningOptionType
Indicates that an entity offers or is associated with a specific type or category of dining option (e.g., dine-in, takeout, delivery).
-
E.
hasReceptionHall
Indicates that one entity possesses or includes a reception hall as part of its facilities or structure.
- 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6632b2de48190abe2b277d89eb695 |
completed | April 20, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:37 p.m.