Triple
T18383216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing Subway Line 16 |
E446508
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Erligou 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: Erligou Station | Statement: [Beijing Subway Line 16, hasStation, Erligou Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erligou Station Context triple: [Beijing Subway Line 16, hasStation, Erligou Station]
-
A.
Erligou station
chosen
Erligou station is a subway station in Beijing that serves passengers on the city's urban rail network.
-
B.
Qiyan station
Qiyan station is a metro station on the Taipei Metro system in Taipei, Taiwan.
-
C.
Xierqi Station
Xierqi Station is a major interchange station on the Beijing Subway, serving as a key hub for commuters in the city’s northern high-tech and residential areas.
-
D.
Zuoying Station
Zuoying Station is a major transportation hub in Kaohsiung, Taiwan, serving high-speed rail, conventional rail, and metro services.
-
E.
Zhuwei station
Zhuwei station is a metro station in New Taipei, Taiwan, serving passengers on Taipei Metro’s Tamsui–Xinyi line.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e5179c931c8190b1c7c8284f42f7b7 |
completed | April 19, 2026, 5:57 p.m. |
Created at: April 10, 2026, 10:45 a.m.