Triple
T5553192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 湘南新宿ライン |
E145575
|
entity |
| Predicate | 経由地 |
P54144
|
FINISHED |
| Object | 東京都心 |
—
|
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: 東京都心 | Statement: [湘南新宿ライン, 経由地, 東京都心]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 経由地 Context triple: [湘南新宿ライン, 経由地, 東京都心]
-
A.
passesThroughCountry
Indicates that a route, path, or object traverses or crosses within the boundaries of a specified country.
-
B.
connectedToMainlandBy
Indicates that one landmass or area is physically linked to a mainland, typically via a bridge, causeway, or other continuous connection.
-
C.
travelsThrough
chosen
Indicates that something moves along, passes across, or is routed via a particular path, medium, or location.
-
D.
servesAsCargoHubFor
Indicates that one entity functions as a central location or facility for handling, consolidating, and distributing cargo associated with another entity.
-
E.
servesAsThroughStationFor
Indicates that a station functions as an intermediate (through) stop for a particular service, route, or journey rather than as its starting or ending point.
- 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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01ff9c9c48190b5e587d58c6515d8 |
completed | March 22, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69c01b0e72f08190bf705d8fe1639401 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:35 p.m.