Triple
T13903333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hangzhou Metro |
E334282
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Hangzhou railway station |
E336895
|
NE 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: Hangzhou railway station | Statement: [Hangzhou Metro, connectsTo, Hangzhou railway station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hangzhou railway station Context triple: [Hangzhou Metro, connectsTo, Hangzhou railway station]
-
A.
Hangzhou railway station
chosen
Hangzhou railway station is a major passenger rail hub in Hangzhou, China, serving as one of the city’s primary gateways for regional and national train services.
-
B.
Hangzhou East railway station
Hangzhou East railway station is a major high-speed rail and transportation hub in Hangzhou, China, serving as one of the country's busiest and most important railway stations.
-
C.
Xihu Station
Xihu Station is a metro station in Taipei, Taiwan, serving the Neihu District and providing access to nearby commercial and entertainment areas.
-
D.
Hangtou station
Hangtou station is a metro station in Shanghai, China, serving passengers on the city’s Line 18.
-
E.
Nanzhou station
Nanzhou station is a metro station in Guangzhou, China, serving as an interchange hub within the city's urban rail network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25db1e308190aaed6a21e443cc44 |
completed | April 14, 2026, 11:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce7638a88190aae1b59c00ee27ce |
completed | May 3, 2026, 10:38 p.m. |
Created at: April 9, 2026, 10:16 p.m.