Triple
T1695644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District of Altenburger Land |
E36650
|
entity |
| Predicate | hasUrbanCenter |
P2106
|
FINISHED |
| Object |
Meuselwitz
Meuselwitz is a small town in the German state of Thuringia, known historically for its lignite mining and industrial heritage.
|
E196341
|
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: Meuselwitz | Statement: [District of Altenburger Land, hasUrbanCenter, Meuselwitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meuselwitz Context triple: [District of Altenburger Land, hasUrbanCenter, Meuselwitz]
-
A.
Sachsenhausen
Sachsenhausen is a historic and culturally vibrant district of Frankfurt am Main, known for its traditional apple wine taverns, museums, and picturesque old town streets.
-
B.
Spandau
Spandau is a western borough of Berlin, Germany, known for its historic old town, fortress, and role as an important residential and industrial district.
-
C.
Degendorf
Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
-
D.
Dessau
Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
-
E.
Schönhausen
Schönhausen is a village in Saxony-Anhalt, Germany, best known as the birthplace of 19th-century statesman Otto von Bismarck.
- 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: Meuselwitz Triple: [District of Altenburger Land, hasUrbanCenter, Meuselwitz]
Generated description
Meuselwitz is a small town in the German state of Thuringia, known historically for its lignite mining and industrial heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Meuselwitz Target entity description: Meuselwitz is a small town in the German state of Thuringia, known historically for its lignite mining and industrial heritage.
-
A.
Sachsenhausen
Sachsenhausen is a historic and culturally vibrant district of Frankfurt am Main, known for its traditional apple wine taverns, museums, and picturesque old town streets.
-
B.
Spandau
Spandau is a western borough of Berlin, Germany, known for its historic old town, fortress, and role as an important residential and industrial district.
-
C.
Degendorf
Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
-
D.
Dessau
Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
-
E.
Schönhausen
Schönhausen is a village in Saxony-Anhalt, Germany, best known as the birthplace of 19th-century statesman Otto von Bismarck.
- 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_69a886163dec8190859c514232a37a05 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa62b645a081909dafdf7a32f2a389 |
completed | March 6, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada0ccf91881909f788d425f66d9eb |
completed | March 8, 2026, 4:16 p.m. |
| NEDg | Description generation | batch_69ada1e13d408190b393c00c331125a2 |
completed | March 8, 2026, 4:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ada292a34c8190a566c2909342ab27 |
completed | March 8, 2026, 4:23 p.m. |
Created at: March 4, 2026, 7:30 p.m.