Triple
T21978714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 前橋駅 |
E542776
|
entity |
| Predicate | 駅コード |
P18202
|
FINISHED |
| Object | 未設定（JR東日本標準の英字略号はMAEなどが用いられる場合がある） |
—
|
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: 未設定（JR東日本標準の英字略号はMAEなどが用いられる場合がある） | Statement: [前橋駅, 駅コード, 未設定（JR東日本標準の英字略号はMAEなどが用いられる場合がある）]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 駅コード Context triple: [前橋駅, 駅コード, 未設定（JR東日本標準の英字略号はMAEなどが用いられる場合がある）]
-
A.
TokyuStationNumber
Indicates that an entity is assigned a specific station number within the Tokyu railway network.
-
B.
railroadCodeFor
chosen
Indicates that a specific railroad code is assigned to or used to identify a particular railroad entity.
-
C.
TokyoMetroStationNumber
Indicates that an entity is assigned a specific official station number within the Tokyo Metro railway network.
-
D.
railwayCodeType
Indicates the specific classification or type category assigned to a railway code within a railway coding system.
-
E.
ToeiSubwayStationNumber
Indicates the identification number assigned to a station within the Toei Subway system.
- 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_69e0c48070988190909db97667b9a0ac |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1248a60708190a9aa8b9b7738c261 |
completed | April 28, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69e6f6154e408190acc5b2c278acaff4 |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:03 p.m.