Triple
T34771622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L0 Series maglev trainsets |
E1002376
|
entity |
| Predicate | plannedCommercialRoute |
P191605
|
FINISHED |
| Object | Tokyo–Nagoya |
—
|
NE NERFINISHED |
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: Tokyo–Nagoya | Statement: [L0 Series maglev trainsets, plannedCommercialRoute, Tokyo–Nagoya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plannedCommercialRoute Context triple: [L0 Series maglev trainsets, plannedCommercialRoute, Tokyo–Nagoya]
-
A.
flightRoute
Indicates a path or sequence of locations that a particular flight travels between, typically from its origin to its destination (and possibly via intermediate stops).
-
B.
operatesLongHaulRouteFrom
Indicates that an entity (typically a transportation carrier) runs long-distance routes originating from a specified location.
-
C.
primaryMarketedRouteName
Indicates the main route or method by which a product is marketed or delivered to its intended users.
-
D.
operatedRoutes
Indicates that an agent (such as a company or organization) runs or manages specific routes, typically providing services along those paths.
-
E.
primaryAirlineRoutesTo
Indicates that one airline serves as the main carrier operating direct or regular flight routes to a particular destination or airport.
- 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_69f76db20dac8190b1e8d0ca4dc1d59f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
| PDg | Predicate description generation | batch_69fce28a74508190aab36551094e8226 |
completed | May 7, 2026, 7:05 p.m. |
Created at: May 3, 2026, 3:59 p.m.