Triple
T1126191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Metro Ginza Line |
E24724
|
entity |
| Predicate | throughServicesWithOtherOperators |
P25258
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Tokyo Metro Ginza Line, throughServicesWithOtherOperators, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: throughServicesWithOtherOperators Context triple: [Tokyo Metro Ginza Line, throughServicesWithOtherOperators, no]
-
A.
otherOperator
Indicates a relationship where one operator is distinguished from, or serves as an alternative to, another operator within the same context or system.
-
B.
operatesServiceTo
Indicates that one entity runs or provides a transportation or service route to another entity or location.
-
C.
operatesService
Indicates that an agent runs, manages, or provides a particular service.
-
D.
operatesBy
Indicates that an entity performs its function, action, or process through the use or application of another entity (e.g., a method, mechanism, or principle).
-
E.
coOperator
Indicates that two or more entities work together as partners or collaborators in performing an activity or achieving a shared objective.
- F. None of above. chosen
Provenance (4 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4749ac8190b0fbddac2e9b2586 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bc47fce48190825d3a877251f789 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:44 p.m.