Triple
T21978739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 前橋駅 |
E542776
|
entity |
| Predicate | 列車種別 |
P56947
|
FINISHED |
| Object | 両毛線の普通列車が停車 |
—
|
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: 両毛線の普通列車が停車 | Statement: [前橋駅, 列車種別, 両毛線の普通列車が停車]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 列車種別 Context triple: [前橋駅, 列車種別, 両毛線の普通列車が停車]
-
A.
trainTypeUsed
chosen
Indicates that a specific type or category of train is employed or operated in a given context or service.
-
B.
railwayClass
Indicates the specific classification or category assigned to a railway or railway service within a defined system.
-
C.
trainsCategory
Indicates that one entity is a category or type under which the other entity is trained or classified.
-
D.
railroadClass
Indicates the classification or category of a railroad according to an established system (e.g., by size, revenue, or regulatory status).
-
E.
speedClassOfTrains
Indicates the classification of trains based on their operating speed or speed category.
- 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.