Triple
T13110724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuhberg (Schöneck) |
E310962
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
town of Schöneck
The town of Schöneck is a small municipality in the Vogtland region of Saxony, Germany, known for its elevated location and surrounding hilly, forested landscape.
|
E1023076
|
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: town of Schöneck | Statement: [Kuhberg (Schöneck), near, town of Schöneck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: town of Schöneck Context triple: [Kuhberg (Schöneck), near, town of Schöneck]
-
A.
Schattdorf
Schattdorf is a Swiss municipality located in the central Alpine canton of Uri.
-
B.
Schneppenhausen
Schneppenhausen is a village and district of the town of Weiterstadt in the German state of Hesse.
-
C.
Schmöckwitz
Schmöckwitz is a locality in the southeastern outskirts of Berlin, known for its lakeside setting and forested surroundings within the borough of Treptow-Köpenick.
-
D.
Nettersheim
Nettersheim is a municipality in the Eifel region of North Rhine-Westphalia, Germany, known for its natural landscapes and archaeological sites.
-
E.
Burgstädt
Burgstädt is a small town in the German state of Saxony, known for its traditional architecture and location near the city of Chemnitz.
- 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: town of Schöneck Triple: [Kuhberg (Schöneck), near, town of Schöneck]
Generated description
The town of Schöneck is a small municipality in the Vogtland region of Saxony, Germany, known for its elevated location and surrounding hilly, forested landscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: town of Schöneck Target entity description: The town of Schöneck is a small municipality in the Vogtland region of Saxony, Germany, known for its elevated location and surrounding hilly, forested landscape.
-
A.
Schattdorf
Schattdorf is a Swiss municipality located in the central Alpine canton of Uri.
-
B.
Schneppenhausen
Schneppenhausen is a village and district of the town of Weiterstadt in the German state of Hesse.
-
C.
Schmöckwitz
Schmöckwitz is a locality in the southeastern outskirts of Berlin, known for its lakeside setting and forested surroundings within the borough of Treptow-Köpenick.
-
D.
Nettersheim
Nettersheim is a municipality in the Eifel region of North Rhine-Westphalia, Germany, known for its natural landscapes and archaeological sites.
-
E.
Burgstädt
Burgstädt is a small town in the German state of Saxony, known for its traditional architecture and location near the city of Chemnitz.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9817e4f408190b77c198b4157d77a |
completed | April 10, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e27d8110819087ade3537f867ae0 |
completed | May 3, 2026, 5:51 a.m. |
| NEDg | Description generation | batch_69f6e4c5e2888190b0bfcdf2cc25ad5f |
completed | May 3, 2026, 6:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6e5979df881909db42a735b9b1064 |
completed | May 3, 2026, 6:05 a.m. |
Created at: April 9, 2026, 9:05 p.m.