Triple
T22440446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 半蔵門 |
E554739
|
entity |
| Predicate | 交通上の役割 |
P25845
|
FINISHED |
| Object | 皇居周辺道路の出入口 |
—
|
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: 皇居周辺道路の出入口 | Statement: [半蔵門, 交通上の役割, 皇居周辺道路の出入口]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 交通上の役割 Context triple: [半蔵門, 交通上の役割, 皇居周辺道路の出入口]
-
A.
transportationRole
Indicates a role or function that an entity has specifically in the context of providing, operating, or supporting transportation.
-
B.
hasMajorTransportationRole
Indicates that an entity plays a primary or significant role in providing or supporting transportation services or infrastructure.
-
C.
roadSystemRole
chosen
Indicates the specific functional role or responsibility an entity has within a road or transportation network system.
-
D.
transportRole
Indicates that an entity participates in a transportation process with a specific functional role (e.g., carrier, passenger, cargo, or operator).
-
E.
facilitatesTrafficFlowBetween
Indicates that one entity enables, supports, or improves the movement of traffic between two other entities or locations.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae1f82881908a611f134eb03f3d |
completed | April 29, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:47 p.m.