Triple
T33077082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | スカイライナー |
E846393
|
entity |
| Predicate | 途中経由線区 |
P848
|
FINISHED |
| Object | 北総線・成田スカイアクセス線経由 |
—
|
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: 北総線・成田スカイアクセス線経由 | Statement: [スカイライナー, 途中経由線区, 北総線・成田スカイアクセス線経由]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 途中経由線区 Context triple: [スカイライナー, 途中経由線区, 北総線・成田スカイアクセス線経由]
-
A.
railwayLine
chosen
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
-
B.
hasCommercialCorridorAlong
Indicates that a place contains a continuous stretch of commercial activity or businesses situated along a specified linear feature, such as a street or route.
-
C.
travelsThrough
Indicates that something moves along, passes across, or is routed via a particular path, medium, or location.
-
D.
isSegmentOfNationalRoute
Indicates that a road segment forms part of a designated national route within a country's road network.
-
E.
servesRailTrafficBetween
Indicates that something (typically a rail line, service, or facility) provides rail transportation connecting two or more 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_69f3495405b88190967af2157b43b896 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:25 a.m.