Triple
T12801785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chuo Shinkansen (maglev) planning and construction |
E306035
|
entity |
| Predicate | plannedStartStation |
P17223
|
FINISHED |
| Object | Tokyo Station vicinity |
—
|
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: Tokyo Station vicinity | Statement: [Chuo Shinkansen (maglev) planning and construction, plannedStartStation, Tokyo Station vicinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plannedStartStation Context triple: [Chuo Shinkansen (maglev) planning and construction, plannedStartStation, Tokyo Station vicinity]
-
A.
startingStation
chosen
Indicates the station or location where a journey, route, or trip begins.
-
B.
stationName
Indicates the name assigned to a particular station in the relationship.
-
C.
terminusStation
Indicates that a station serves as the final endpoint or terminal stop for a given route or service.
-
D.
endStationProvidesAccessTo
Indicates that a particular end station offers access or connectivity to another location, service, or network resource.
-
E.
accessibleFromStation
Indicates that a location or facility can be reached directly or conveniently starting from a given station.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e7d3f5c8190bf01bef5d263ca26 |
completed | April 10, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69d9640ed7448190b276e7fab649f7d2 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:30 p.m.