Triple
T22440439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 半蔵門 |
E554739
|
entity |
| Predicate | 最寄り鉄道路線 |
P25223
|
FINISHED |
| Object | 東京メトロ半蔵門線 |
—
|
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: 東京メトロ半蔵門線 | Statement: [半蔵門, 最寄り鉄道路線, 東京メトロ半蔵門線]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 最寄り鉄道路線 Context triple: [半蔵門, 最寄り鉄道路線, 東京メトロ半蔵門線]
-
A.
nearestRailwayLine
chosen
Indicates that one railway line is the closest in distance to a given location or feature compared to all other railway lines.
-
B.
nearestShinkansenStation
Indicates that one entity is the Shinkansen (bullet train) station geographically closest to the other entity.
-
C.
nearestCommuterRailLine
Indicates the commuter rail line that is geographically closest to a given location or entity.
-
D.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
-
E.
railwayTypeServed
Indicates the type of railway system or service that a given entity (such as a station, line, or facility) is designed to serve or accommodate.
- 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.