Triple
T14249213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 赤坂御用地 |
E353212
|
entity |
| Predicate | 関連施設種別 |
P81092
|
FINISHED |
| Object | 御所 |
—
|
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: 御所 | Statement: [赤坂御用地, 関連施設種別, 御所]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連施設種別 Context triple: [赤坂御用地, 関連施設種別, 御所]
-
A.
関連施設
chosen
Indicates a relationship where one facility is associated with, connected to, or otherwise related to another facility.
-
B.
associatedSpaceFacility
Indicates that there is a relationship linking an entity to a specific space-related facility with which it is connected or involved.
-
C.
designedFacilityType
Indicates the type or category of facility that something (such as a plan, system, or component) is specifically designed for.
-
D.
relatedInfrastructure
Indicates that one piece of infrastructure is connected, associated, or functionally related to another infrastructure element.
-
E.
appliesToFacility
Indicates that something (such as a rule, policy, condition, or attribute) is relevant to, valid for, or in effect at a particular facility.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6295ef9081909cfb0c1283bca21a |
completed | April 14, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69de05c09b7881908acbca18bd7d997c |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:08 a.m.