Triple
T5553190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 湘南新宿ライン |
E145575
|
entity |
| Predicate | 運行形態 |
P26963
|
FINISHED |
| Object | 系統運転 |
—
|
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: 系統運転 | Statement: [湘南新宿ライン, 運行形態, 系統運転]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 運行形態 Context triple: [湘南新宿ライン, 運行形態, 系統運転]
-
A.
operatingPattern
chosen
Indicates the characteristic way in which an entity functions or operates over time, such as its typical mode, schedule, or behavioral pattern.
-
B.
operatingModel
Indicates how an organization structures and manages its processes, resources, and governance to deliver its products or services.
-
C.
operatingStatus
Indicates whether an entity is currently functioning, active, or in service versus inactive, closed, or out of service.
-
D.
operatingCondition
Indicates the specific state, requirements, or circumstances under which an entity functions or is intended to be used.
-
E.
operationalForm
Indicates that one entity is the specific operational or executable form of another, more abstract entity.
- 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.