Triple
T9540723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelheim (district) |
E230148
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Riedenburg
Riedenburg is a small Bavarian town in southern Germany known for its scenic location in the Altmühl Valley and its historic castles.
|
E832455
|
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: Riedenburg | Statement: [Kelheim (district), containsTown, Riedenburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Riedenburg Context triple: [Kelheim (district), containsTown, Riedenburg]
-
A.
Lankwitz
Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
-
B.
Oranienburg
Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
-
C.
Markranstädt
Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
-
D.
Eilenburg
Eilenburg is a small historic town in the German state of Saxony, situated on the Mulde River northeast of Leipzig.
-
E.
Trakehnen
Trakehnen was a renowned East Prussian stud farm and village, historically famous as the cradle of the Trakehner horse breed.
- 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: Riedenburg Triple: [Kelheim (district), containsTown, Riedenburg]
Generated description
Riedenburg is a small Bavarian town in southern Germany known for its scenic location in the Altmühl Valley and its historic castles.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Riedenburg Target entity description: Riedenburg is a small Bavarian town in southern Germany known for its scenic location in the Altmühl Valley and its historic castles.
-
A.
Lankwitz
Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
-
B.
Oranienburg
Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
-
C.
Markranstädt
Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
-
D.
Eilenburg
Eilenburg is a small historic town in the German state of Saxony, situated on the Mulde River northeast of Leipzig.
-
E.
Trakehnen
Trakehnen was a renowned East Prussian stud farm and village, historically famous as the cradle of the Trakehner horse breed.
- 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_69d23caf70f8819090ba25c4395c3de2 |
completed | April 5, 2026, 10:42 a.m. |
| NEDg | Description generation | batch_69d23e6ca3908190b7ad7b932ab35ad7 |
completed | April 5, 2026, 10:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d241020074819092bc2deea85a6ac0 |
completed | April 5, 2026, 11:01 a.m. |
Created at: March 30, 2026, 8:01 p.m.