Triple
T1743556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai South Railway Station |
E38284
|
entity |
| Predicate | servesAsThroughStationFor |
P32039
|
FINISHED |
| Object | many intercity services |
—
|
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: many intercity services | Statement: [Shanghai South Railway Station, servesAsThroughStationFor, many intercity services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesAsThroughStationFor Context triple: [Shanghai South Railway Station, servesAsThroughStationFor, many intercity services]
-
A.
interchangeStation
Indicates a station where passengers can transfer between different routes, lines, or modes of transportation.
-
B.
junctionStation
Indicates that a station functions as a junction where multiple routes or lines intersect or connect.
-
C.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
D.
terminusStation
Indicates that a station serves as the final endpoint or terminal stop for a given route or service.
-
E.
stationType
Indicates the specific category or classification of a station based on its function, services, or operational characteristics.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab630e7d008190a8c673665d9672bb |
completed | March 6, 2026, 11:28 p.m. |
| PD | Predicate disambiguation | batch_69aa61c5a18481909bc49e0c54d64314 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab630cb34881908c9fb7ed5dedcd77 |
completed | March 6, 2026, 11:28 p.m. |
Created at: March 4, 2026, 7:31 p.m.