Triple
T10450778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berliner Bezirk Spandau |
E246414
|
entity |
| Predicate | hasGreenSpace |
P1495
|
FINISHED |
| Object |
Haveluferanlagen
Haveluferanlagen is a riverside green space and recreational park area along the Havel in Berlin’s Spandau district.
|
E863347
|
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: Haveluferanlagen | Statement: [Berliner Bezirk Spandau, hasGreenSpace, Haveluferanlagen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haveluferanlagen Context triple: [Berliner Bezirk Spandau, hasGreenSpace, Haveluferanlagen]
-
A.
Eggermühlen
Eggermühlen is a small rural municipality in Lower Saxony, Germany, situated within the Osnabrück district.
-
B.
Plöckenstein
Plöckenstein is a mountain on the border of Austria, Germany, and the Czech Republic, known as the highest peak of the Bohemian Forest.
-
C.
Weiherhammer
Weiherhammer is a small municipality in the Upper Palatinate region of Bavaria, Germany, known for its rural character and local industry.
-
D.
Rotherbaum
Rotherbaum is a central, upscale district of Hamburg, Germany, known for its elegant residential areas, cultural institutions, and proximity to the Alster lakes.
-
E.
Oberhauser
Oberhauser is a German-language surname borne by various notable individuals across fields such as sports, the arts, and public life.
- 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: Haveluferanlagen Triple: [Berliner Bezirk Spandau, hasGreenSpace, Haveluferanlagen]
Generated description
Haveluferanlagen is a riverside green space and recreational park area along the Havel in Berlin’s Spandau district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Haveluferanlagen Target entity description: Haveluferanlagen is a riverside green space and recreational park area along the Havel in Berlin’s Spandau district.
-
A.
Eggermühlen
Eggermühlen is a small rural municipality in Lower Saxony, Germany, situated within the Osnabrück district.
-
B.
Plöckenstein
Plöckenstein is a mountain on the border of Austria, Germany, and the Czech Republic, known as the highest peak of the Bohemian Forest.
-
C.
Weiherhammer
Weiherhammer is a small municipality in the Upper Palatinate region of Bavaria, Germany, known for its rural character and local industry.
-
D.
Rotherbaum
Rotherbaum is a central, upscale district of Hamburg, Germany, known for its elegant residential areas, cultural institutions, and proximity to the Alster lakes.
-
E.
Oberhauser
Oberhauser is a German-language surname borne by various notable individuals across fields such as sports, the arts, and public life.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe0a6a548190a54212912f618e4e |
completed | April 7, 2026, 12:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87efedf6c8190aa4b7bbe5f160eeb |
completed | April 10, 2026, 4:39 a.m. |
| NEDg | Description generation | batch_69d886c562c081908aae846da8efb1a5 |
completed | April 10, 2026, 5:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d88dce21448190b093b4f548e29f84 |
completed | April 10, 2026, 5:42 a.m. |
Created at: April 6, 2026, 12:17 p.m.