Triple
T20574535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vienna–Gänserndorf railway line |
E505179
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Gänserndorf |
—
|
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: Gänserndorf | Statement: [Vienna–Gänserndorf railway line, connects, Gänserndorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gänserndorf Context triple: [Vienna–Gänserndorf railway line, connects, Gänserndorf]
-
A.
Gänserndorf
chosen
Gänserndorf is a town in Lower Austria that serves as a regional center on the eastern edge of the Marchfeld plain, northeast of Vienna.
-
B.
Gneixendorf
Gneixendorf is a village and cadastral community that forms part of the city of Krems an der Donau in Lower Austria.
-
C.
Parndorf
Parndorf is a town in eastern Austria’s Burgenland region, known for its large designer outlet shopping center and proximity to major transport routes.
-
D.
Kiliansdorf
Kiliansdorf is a village and district of the town of Roth in the Bavarian region of Germany.
-
E.
Seifhennersdorf
Seifhennersdorf is a small town in the Görlitz district of Saxony in eastern Germany, near the Czech border.
- 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_69e0b4b721588190993ac7b0a9be2736 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a9087af88190a4610ecb29f637ca |
completed | April 20, 2026, 10:30 p.m. |
Created at: April 16, 2026, 11:39 a.m.