Triple
T23320647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South-Link Line |
E591140
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Fangliao Station |
—
|
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: Fangliao Station | Statement: [South-Link Line, terminus, Fangliao Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fangliao Station Context triple: [South-Link Line, terminus, Fangliao Station]
-
A.
Fangliao Station
chosen
Fangliao Station is a railway station in southern Taiwan that serves as a key transit point for passengers traveling through Pingtung County and toward the southern tip of the island.
-
B.
Zuoying Station
Zuoying Station is a major transportation hub in Kaohsiung, Taiwan, serving high-speed rail, conventional rail, and metro services.
-
C.
Liyuan Station
Liyuan Station is a stop on Beijing's Batong Line serving the eastern suburbs of the city.
-
D.
Laojie station
Laojie station is a major interchange and one of the busiest metro stations in Shenzhen, China, serving the city’s central commercial and shopping districts.
-
E.
Luyuan station
Luyuan station is a subway station on Beijing's Line 8 serving passengers in the city's urban transit network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d1effe4819096907f95f610dbff |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19785ae5481908816b37da95ceb3e |
completed | April 29, 2026, 5:30 a.m. |
Created at: April 17, 2026, 5:07 p.m.