Triple
T2926543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barnim (district) |
E78857
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Bernau bei Berlin
Bernau bei Berlin is a historic town in the German state of Brandenburg, located just northeast of Berlin and known for its well-preserved medieval city walls.
|
E311039
|
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: Bernau bei Berlin | Statement: [Barnim (district), contains, Bernau bei Berlin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bernau bei Berlin Context triple: [Barnim (district), contains, Bernau bei Berlin]
-
A.
Degendorf
Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
-
B.
Grevesmühlen
Grevesmühlen is a small town in the German state of Mecklenburg-Vorpommern, known as a local administrative and service center in the north of the country.
-
C.
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.
-
D.
Schönhausen
Schönhausen is a village in Saxony-Anhalt, Germany, best known as the birthplace of 19th-century statesman Otto von Bismarck.
-
E.
Schkopau
Schkopau is a municipality in the Saalekreis district of Saxony-Anhalt, Germany, known for its large chemical industry complex.
- 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: Bernau bei Berlin Triple: [Barnim (district), contains, Bernau bei Berlin]
Generated description
Bernau bei Berlin is a historic town in the German state of Brandenburg, located just northeast of Berlin and known for its well-preserved medieval city walls.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bernau bei Berlin Target entity description: Bernau bei Berlin is a historic town in the German state of Brandenburg, located just northeast of Berlin and known for its well-preserved medieval city walls.
-
A.
Degendorf
Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
-
B.
Grevesmühlen
Grevesmühlen is a small town in the German state of Mecklenburg-Vorpommern, known as a local administrative and service center in the north of the country.
-
C.
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.
-
D.
Schönhausen
Schönhausen is a village in Saxony-Anhalt, Germany, best known as the birthplace of 19th-century statesman Otto von Bismarck.
-
E.
Schkopau
Schkopau is a municipality in the Saalekreis district of Saxony-Anhalt, Germany, known for its large chemical industry complex.
- 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_69ad8b0d40b481908bc2a5fa2e73c3fb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97c1e9c08190bcec80bc3262697a |
completed | March 8, 2026, 3:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b08668a204819082b13e6ce62d5728 |
completed | March 10, 2026, 9 p.m. |
| NEDg | Description generation | batch_69b0d18f7928819098fba6a23dd40230 |
completed | March 11, 2026, 2:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0d221ec2481909c9d42f1c0d86b9b |
completed | March 11, 2026, 2:23 a.m. |
Created at: March 8, 2026, 2:55 p.m.