Triple
T2926544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barnim (district) |
E78857
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Wandlitz
Wandlitz is a municipality in the German state of Brandenburg, known for its lakes, forests, and proximity to Berlin.
|
E311040
|
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: Wandlitz | Statement: [Barnim (district), contains, Wandlitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wandlitz Context triple: [Barnim (district), contains, Wandlitz]
-
A.
Fürstenwalde
Fürstenwalde is a town in eastern Germany’s Brandenburg region, known for its location on the River Spree and its historic churches and medieval architecture.
-
B.
Neustrelitz
Neustrelitz is a town in northeastern Germany known for hosting a key research center of the German Aerospace Center (DLR), particularly focused on satellite data and space-related technologies.
-
C.
Lichterfelde
Lichterfelde is a residential district in southwestern Berlin known for its historic villas, leafy streets, and affluent character.
-
D.
Oranienburg
Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
-
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: Wandlitz Triple: [Barnim (district), contains, Wandlitz]
Generated description
Wandlitz is a municipality in the German state of Brandenburg, known for its lakes, forests, and proximity to Berlin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wandlitz Target entity description: Wandlitz is a municipality in the German state of Brandenburg, known for its lakes, forests, and proximity to Berlin.
-
A.
Fürstenwalde
Fürstenwalde is a town in eastern Germany’s Brandenburg region, known for its location on the River Spree and its historic churches and medieval architecture.
-
B.
Neustrelitz
Neustrelitz is a town in northeastern Germany known for hosting a key research center of the German Aerospace Center (DLR), particularly focused on satellite data and space-related technologies.
-
C.
Lichterfelde
Lichterfelde is a residential district in southwestern Berlin known for its historic villas, leafy streets, and affluent character.
-
D.
Oranienburg
Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
-
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.