Triple
T7721576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wiener Neustadt |
E175023
|
entity |
| Predicate | demonym |
P191
|
FINISHED |
| Object | Wiener Neustädter |
E175023
|
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: Wiener Neustädter | Statement: [Wiener Neustadt, demonym, Wiener Neustädter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wiener Neustädter Context triple: [Wiener Neustadt, demonym, Wiener Neustädter]
-
A.
Wiener Neustadt
chosen
Wiener Neustadt is a historic city in Lower Austria known as a former imperial residence and military stronghold south of Vienna.
-
B.
Schwechat
Schwechat is an Austrian town just southeast of Vienna, best known as the site of Vienna International Airport and a major hub for industry and transport.
-
C.
Seibersdorf
Seibersdorf is an Austrian town known for hosting major research and testing laboratories of the International Atomic Energy Agency.
-
D.
Baden bei Wien
Baden bei Wien is a historic spa town in eastern Austria renowned for its thermal springs, Biedermeier architecture, and proximity to Vienna.
-
E.
Donaustadt
Donaustadt is the 22nd district of Vienna, Austria, known for its extensive residential areas, modern developments, and the location of the Vienna International Centre.
- 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702f1786881908b025d8986e5f1fa |
completed | March 27, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8ef0465a4819095c34584e8f80739 |
completed | March 29, 2026, 9:21 a.m. |
Created at: March 27, 2026, 4:05 p.m.