Triple
T16386202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taipei Metro Wenhu line |
E397927
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Daan station |
E1169937
|
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: Daan station | Statement: [Taipei Metro Wenhu line, hasStation, Daan station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daan station Context triple: [Taipei Metro Wenhu line, hasStation, Daan station]
-
A.
Daan station
chosen
Daan station is a metro station in Taipei, Taiwan, serving as an interchange hub on the city’s rapid transit network.
-
B.
Europaplein station
Europaplein station is an underground Amsterdam Metro station in the Zuidas district that serves as a stop on the North–South Line (Line 52).
-
C.
Den Dolder railway station
Den Dolder railway station is a local train station in the village of Den Dolder in the Netherlands, serving as a stop on regional rail services in the province of Utrecht.
-
D.
Beekkant station
Beekkant station is a Brussels Metro interchange station in the municipality of Molenbeek-Saint-Jean, serving multiple metro lines on the western side of the city.
-
E.
Spuyten Duyvil station
Spuyten Duyvil station is a Metro-North Railroad commuter rail stop in the Bronx, New York City, providing Hudson Line service along the Hudson River.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e3263d260081909db9ac6016d5738a |
completed | April 18, 2026, 6:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00356cf44081909133b599cfe9ed4a |
completed | May 10, 2026, 7:36 a.m. |
Created at: April 10, 2026, 5:08 a.m.