Triple
T21974799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Budaörs |
E542675
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Vösendorf
Vösendorf is a market town in Lower Austria, just south of Vienna, known for its large shopping centers and proximity to the capital.
|
E1522581
|
NE FINISHED |
How this triple was built (4 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: Vösendorf | Statement: [Budaörs, hasTwinTown, Vösendorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vösendorf Context triple: [Budaörs, hasTwinTown, Vösendorf]
-
A.
Vöcklabruck
Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
-
B.
Gumpoldskirchen
Gumpoldskirchen is a historic wine-growing town in Lower Austria, renowned for its traditional vineyards and picturesque setting near Vienna.
-
C.
Patersdorf
Patersdorf is a small municipality in the Bavarian Forest region of southeastern Germany.
-
D.
Mauterndorf
Mauterndorf is a historic market town in the Austrian state of Salzburg, known for its well-preserved medieval castle and alpine setting in the Lungau region.
-
E.
Traiskirchen
Traiskirchen is a town in Lower Austria best known internationally for hosting one of Austria’s largest refugee reception centers.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Vösendorf Triple: [Budaörs, hasTwinTown, Vösendorf]
Generated description
Vösendorf is a market town in Lower Austria, just south of Vienna, known for its large shopping centers and proximity to the capital.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vösendorf Target entity description: Vösendorf is a market town in Lower Austria, just south of Vienna, known for its large shopping centers and proximity to the capital.
-
A.
Vöcklabruck
Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
-
B.
Gumpoldskirchen
Gumpoldskirchen is a historic wine-growing town in Lower Austria, renowned for its traditional vineyards and picturesque setting near Vienna.
-
C.
Patersdorf
Patersdorf is a small municipality in the Bavarian Forest region of southeastern Germany.
-
D.
Mauterndorf
Mauterndorf is a historic market town in the Austrian state of Salzburg, known for its well-preserved medieval castle and alpine setting in the Lungau region.
-
E.
Traiskirchen
Traiskirchen is a town in Lower Austria best known internationally for hosting one of Austria’s largest refugee reception centers.
- F. None of above. chosen
Provenance (5 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_69e0c48070988190909db97667b9a0ac |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12487a1a88190abb8a51fcd533b6a |
completed | April 28, 2026, 9:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a9eaa53cc8190bfc006245a63f9e5 |
completed | May 18, 2026, 5:07 a.m. |
| NEDg | Description generation | batch_6a0aa0066d0481909872d8e1dbbe2fcf |
completed | May 18, 2026, 5:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0aa07acd5c8190bc73cc1d8897fa01 |
completed | May 18, 2026, 5:15 a.m. |
Created at: April 16, 2026, 8:03 p.m.