Triple
T6032195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hochsauerlandkreis |
E134331
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Winterberg
Winterberg is a German town in the Rothaar Mountains of North Rhine-Westphalia, known as a popular winter sports and holiday resort.
|
E564061
|
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: Winterberg | Statement: [Hochsauerlandkreis, containsTown, Winterberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Winterberg Context triple: [Hochsauerlandkreis, containsTown, Winterberg]
-
A.
Klingenthal
Klingenthal is a small town in the Vogtland region of Saxony, Germany, known for its long tradition of musical instrument making, especially accordions and brass instruments.
-
B.
Oberhof
Oberhof is a German winter sports town in Thuringia renowned for its biathlon, luge, and cross-country skiing facilities and World Cup events.
-
C.
Seiffen
Seiffen is a village in Germany’s Ore Mountains renowned for its traditional wooden toy-making and iconic Christmas decorations.
-
D.
Treuenbrietzen
Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
-
E.
Johannisberg
Johannisberg is a prominent peak in the Austrian Alps, located in the High Tauern range near the Grossglockner.
- 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: Winterberg Triple: [Hochsauerlandkreis, containsTown, Winterberg]
Generated description
Winterberg is a German town in the Rothaar Mountains of North Rhine-Westphalia, known as a popular winter sports and holiday resort.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Winterberg Target entity description: Winterberg is a German town in the Rothaar Mountains of North Rhine-Westphalia, known as a popular winter sports and holiday resort.
-
A.
Klingenthal
Klingenthal is a small town in the Vogtland region of Saxony, Germany, known for its long tradition of musical instrument making, especially accordions and brass instruments.
-
B.
Oberhof
Oberhof is a German winter sports town in Thuringia renowned for its biathlon, luge, and cross-country skiing facilities and World Cup events.
-
C.
Seiffen
Seiffen is a village in Germany’s Ore Mountains renowned for its traditional wooden toy-making and iconic Christmas decorations.
-
D.
Treuenbrietzen
Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
-
E.
Johannisberg
Johannisberg is a prominent peak in the Austrian Alps, located in the High Tauern range near the Grossglockner.
- 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056b0a8d081909035e2e85e851ca1 |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c113855ad08190b9ff826a2f39c356 |
completed | March 23, 2026, 10:18 a.m. |
| NEDg | Description generation | batch_69c114ec9d0c819092de76a6712c482d |
completed | March 23, 2026, 10:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c115552c188190b500d96e86410180 |
completed | March 23, 2026, 10:26 a.m. |
Created at: March 22, 2026, 4:08 p.m.