Triple
T9123211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Königsplatz (Berlin) |
E218906
|
entity |
| Predicate | partOfUrbanArea |
P294
|
FINISHED |
| Object |
Spreebogen
Spreebogen is a prominent riverside area in central Berlin known for its sweeping bend of the River Spree and its concentration of major government and cultural buildings.
|
E779624
|
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: Spreebogen | Statement: [Königsplatz (Berlin), partOfUrbanArea, Spreebogen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spreebogen Context triple: [Königsplatz (Berlin), partOfUrbanArea, Spreebogen]
-
A.
Schwibbogen
A Schwibbogen is a traditional German decorative candle arch, typically made of wood and displayed in windows during the Christmas season, especially in the Ore Mountains region.
-
B.
Schwerteck
Schwerteck is a mountain peak in the Glockner Group of the Austrian Alps.
-
C.
Kleeberg
Kleeberg is a Polish surname most notably associated with General Franciszek Kleeberg, a commander in the early stages of World War II.
-
D.
Bösperde
Bösperde is a district of the town of Menden in North Rhine-Westphalia, Germany, known as a primarily residential suburban area.
-
E.
Rinkerode
Rinkerode is a village in North Rhine-Westphalia, Germany, known as a district of the town of Drensteinfurt in the Münster region.
- 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: Spreebogen Triple: [Königsplatz (Berlin), partOfUrbanArea, Spreebogen]
Generated description
Spreebogen is a prominent riverside area in central Berlin known for its sweeping bend of the River Spree and its concentration of major government and cultural buildings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Spreebogen Target entity description: Spreebogen is a prominent riverside area in central Berlin known for its sweeping bend of the River Spree and its concentration of major government and cultural buildings.
-
A.
Schwibbogen
A Schwibbogen is a traditional German decorative candle arch, typically made of wood and displayed in windows during the Christmas season, especially in the Ore Mountains region.
-
B.
Schwerteck
Schwerteck is a mountain peak in the Glockner Group of the Austrian Alps.
-
C.
Kleeberg
Kleeberg is a Polish surname most notably associated with General Franciszek Kleeberg, a commander in the early stages of World War II.
-
D.
Bösperde
Bösperde is a district of the town of Menden in North Rhine-Westphalia, Germany, known as a primarily residential suburban area.
-
E.
Rinkerode
Rinkerode is a village in North Rhine-Westphalia, Germany, known as a district of the town of Drensteinfurt in the Münster region.
- 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_69ca83dddd548190983b96c664f7f367 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8b5fa188190be6465e74cf26915 |
completed | April 1, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0308ff628819083f02bf71eb40c5b |
completed | April 3, 2026, 9:26 p.m. |
| NEDg | Description generation | batch_69d0318ef52c8190bfa0bef6a8d41daa |
completed | April 3, 2026, 9:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d03571c4648190bd546152c61c55a5 |
completed | April 3, 2026, 9:47 p.m. |
Created at: March 30, 2026, 7:17 p.m.