Triple
T9540576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Straubing-Bogen |
E230145
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Bogen
Bogen is a historic town in Lower Bavaria, Germany, situated on the Danube River and known for its medieval heritage and regional significance.
|
E805380
|
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: Bogen | Statement: [Straubing-Bogen, namedAfter, Bogen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bogen Context triple: [Straubing-Bogen, namedAfter, Bogen]
-
A.
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.
-
B.
Bigen
Bigen is one of the small islands that make up Maloelap Atoll in the Marshall Islands, located in the central Pacific Ocean.
-
C.
Lügde
Lügde is a small historic town in North Rhine-Westphalia, Germany, known for its traditional Easter customs and scenic location near the Weser Uplands.
-
D.
Bechtsrieth
Bechtsrieth is a small municipality in the Upper Palatinate region of Bavaria, Germany.
-
E.
Borghorst
Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
- 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: Bogen Triple: [Straubing-Bogen, namedAfter, Bogen]
Generated description
Bogen is a historic town in Lower Bavaria, Germany, situated on the Danube River and known for its medieval heritage and regional significance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bogen Target entity description: Bogen is a historic town in Lower Bavaria, Germany, situated on the Danube River and known for its medieval heritage and regional significance.
-
A.
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.
-
B.
Bigen
Bigen is one of the small islands that make up Maloelap Atoll in the Marshall Islands, located in the central Pacific Ocean.
-
C.
Lügde
Lügde is a small historic town in North Rhine-Westphalia, Germany, known for its traditional Easter customs and scenic location near the Weser Uplands.
-
D.
Bechtsrieth
Bechtsrieth is a small municipality in the Upper Palatinate region of Bavaria, Germany.
-
E.
Borghorst
Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e695948190ab107fff38c57de7 |
completed | April 1, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d14c5da5a081909d646c69d5de8e18 |
completed | April 4, 2026, 5:37 p.m. |
| NEDg | Description generation | batch_69d14d0c39c88190a705470104dc7b80 |
completed | April 4, 2026, 5:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d14d79065081908a4e619c71e0d359 |
completed | April 4, 2026, 5:42 p.m. |
Created at: March 30, 2026, 8:01 p.m.