Triple
T653685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nagoya |
E11598
|
entity |
| Predicate | NagoyaStationIs |
P1071
|
FINISHED |
| Object | one of the world’s largest train stations by floor area |
—
|
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: one of the world’s largest train stations by floor area | Statement: [Nagoya, NagoyaStationIs, one of the world’s largest train stations by floor area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NagoyaStationIs Context triple: [Nagoya, NagoyaStationIs, one of the world’s largest train stations by floor area]
-
A.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
B.
hasRailwayStation
Indicates that a place or location is served by, or contains, a railway station.
-
C.
interchangeStation
Indicates a station where passengers can transfer between different routes, lines, or modes of transportation.
-
D.
hasMajorRailwayStation
chosen
Indicates that a place contains or is served by a principal railway station that functions as a major hub for rail transport.
-
E.
hasBusStation
Indicates that a place or area contains or is served by a bus 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f4a660c8190b887cb4da01ef7ae |
completed | March 1, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69a49d1001088190aa7ca3c8f2ad0e32 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.