Triple
T9826863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krems an der Donau |
E238677
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Landersdorf
Landersdorf is a locality within the city of Krems an der Donau in Lower Austria, known as part of its surrounding wine-growing and rural area.
|
E909723
|
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: Landersdorf | Statement: [Krems an der Donau, hasPart, Landersdorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Landersdorf Context triple: [Krems an der Donau, hasPart, Landersdorf]
-
A.
Hunderdorf
Hunderdorf is a small municipality in the Straubing-Bogen district of Lower Bavaria in southeastern Germany.
-
B.
Lappersdorf
Lappersdorf is a municipality in Bavaria, Germany, located just north of the city of Regensburg and known as a residential and commuter town in the Upper Palatinate region.
-
C.
Langdorf
Langdorf is a small municipality in the Bavarian Forest region of southeastern Germany.
-
D.
Burkhardtsdorf
Burkhardtsdorf is a small municipality in the Erzgebirge (Ore Mountains) region of Saxony, eastern Germany.
-
E.
Heinersdorf
Heinersdorf is a residential locality in the borough of Pankow in Berlin, Germany, known for its suburban character and proximity to the city center.
- 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: Landersdorf Triple: [Krems an der Donau, hasPart, Landersdorf]
Generated description
Landersdorf is a locality within the city of Krems an der Donau in Lower Austria, known as part of its surrounding wine-growing and rural area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Landersdorf Target entity description: Landersdorf is a locality within the city of Krems an der Donau in Lower Austria, known as part of its surrounding wine-growing and rural area.
-
A.
Hunderdorf
Hunderdorf is a small municipality in the Straubing-Bogen district of Lower Bavaria in southeastern Germany.
-
B.
Lappersdorf
Lappersdorf is a municipality in Bavaria, Germany, located just north of the city of Regensburg and known as a residential and commuter town in the Upper Palatinate region.
-
C.
Langdorf
Langdorf is a small municipality in the Bavarian Forest region of southeastern Germany.
-
D.
Burkhardtsdorf
Burkhardtsdorf is a small municipality in the Erzgebirge (Ore Mountains) region of Saxony, eastern Germany.
-
E.
Heinersdorf
Heinersdorf is a residential locality in the borough of Pankow in Berlin, Germany, known for its suburban character and proximity to the city center.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb324e7848190b9424a78ca653afe |
completed | April 2, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e482d55a04819090d95f7a4abb6e29 |
completed | April 19, 2026, 7:23 a.m. |
| NEDg | Description generation | batch_69e485f46f0c81908dbe5b47322ab7b7 |
completed | April 19, 2026, 7:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4878dd95c81908ceaf91ee46f49c1 |
completed | April 19, 2026, 7:43 a.m. |
Created at: March 30, 2026, 8:32 p.m.