Triple
T14295421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Berlin |
E354425
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Blankenfelde
Blankenfelde is a locality on the southern outskirts of Berlin, Germany, known for its suburban residential character and proximity to both the capital and surrounding Brandenburg countryside.
|
E1091720
|
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: Blankenfelde | Statement: [Northern Berlin, hasPart, Blankenfelde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blankenfelde Context triple: [Northern Berlin, hasPart, Blankenfelde]
-
A.
Blankenfelde
Blankenfelde is a locality within the Berlin borough of Pankow, known for its residential character and proximity to green spaces.
-
B.
Marienfelde
Marienfelde is a locality in the southern part of Berlin known for its residential areas and historical refugee reception center.
-
C.
Blankenburg
Blankenburg is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and village-like atmosphere.
-
D.
Blankenburg
Blankenburg is a town in central Germany, located in the Harz region of the state of Saxony-Anhalt.
-
E.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
- 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: Blankenfelde Triple: [Northern Berlin, hasPart, Blankenfelde]
Generated description
Blankenfelde is a locality on the southern outskirts of Berlin, Germany, known for its suburban residential character and proximity to both the capital and surrounding Brandenburg countryside.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Blankenfelde Target entity description: Blankenfelde is a locality on the southern outskirts of Berlin, Germany, known for its suburban residential character and proximity to both the capital and surrounding Brandenburg countryside.
-
A.
Blankenfelde
Blankenfelde is a locality within the Berlin borough of Pankow, known for its residential character and proximity to green spaces.
-
B.
Marienfelde
Marienfelde is a locality in the southern part of Berlin known for its residential areas and historical refugee reception center.
-
C.
Blankenburg
Blankenburg is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and village-like atmosphere.
-
D.
Blankenburg
Blankenburg is a town in central Germany, located in the Harz region of the state of Saxony-Anhalt.
-
E.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de717b35ec81908968994e65737c66 |
completed | April 14, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d246ccc81909e9fe8b4487dcc88 |
completed | May 8, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69fd3eabe838819099664221953ba756 |
completed | May 8, 2026, 1:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd3f29b2148190931d415d6d5550a6 |
completed | May 8, 2026, 1:40 a.m. |
Created at: April 10, 2026, 1:11 a.m.