Triple
T37061224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 芥川 |
E917328
|
entity |
| Predicate | 関連交通施設 |
P136134
|
FINISHED |
| Object | JR高槻駅周辺の河川空間 |
—
|
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: JR高槻駅周辺の河川空間 | Statement: [芥川, 関連交通施設, JR高槻駅周辺の河川空間]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連交通施設 Context triple: [芥川, 関連交通施設, JR高槻駅周辺の河川空間]
-
A.
関連施設
Indicates a relationship where one facility is associated with, connected to, or otherwise related to another facility.
-
B.
associatedWithTransportationInfrastructure
chosen
Indicates a relationship where something is connected or related to transportation infrastructure, such as facilities, systems, or structures used for transport.
-
C.
transportationFacility
Indicates that one entity is a facility or location used for the transportation or transit of people or goods in relation to another entity.
-
D.
transportInfrastructureFeature
Indicates a relationship where an entity is a specific element or component of transport infrastructure, such as roads, railways, or related facilities.
-
E.
infrastructureAssociatedWith
Indicates a relationship where a piece of infrastructure is functionally or contextually connected to, supports, or is used by another entity.
- 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_69f76e95fa40819091e14681087ae5e4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb34e5576881909394355c8ec6ddd2 |
completed | May 6, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69fb2f6171e88190bf1e0ee6a644b6a9 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:14 p.m.