Triple
T5553196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 湘南新宿ライン |
E145575
|
entity |
| Predicate | 経由路線 |
P11333
|
FINISHED |
| Object | 山手貨物線 |
—
|
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: 山手貨物線 | Statement: [湘南新宿ライン, 経由路線, 山手貨物線]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 経由路線 Context triple: [湘南新宿ライン, 経由路線, 山手貨物線]
-
A.
routeVia
chosen
Indicates that a connection, path, or communication between two points is established or carried out through an intermediate location, node, or channel.
-
B.
hasRailRoute
Indicates that there exists a rail-based transportation route or connection between the related entities.
-
C.
isMostCommonRouteTo
Indicates that one route is the most frequently used or typical way to reach a particular destination or outcome compared to all other possible routes.
-
D.
routeBetween
Indicates that there exists a path or connection enabling travel or communication between two locations or points.
-
E.
isPublicTransportRoute
Indicates that a given route is designated and operated as part of a public transportation system available for general use.
- 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.