Triple
T9540735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelheim (district) |
E230148
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Biburg
Biburg is a small municipality in the Lower Bavarian region of Germany, known for its rural character and historic monastery.
|
E818337
|
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: Biburg | Statement: [Kelheim (district), containsMunicipality, Biburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biburg Context triple: [Kelheim (district), containsMunicipality, Biburg]
-
A.
Kollnburg
Kollnburg is a small municipality in the Bavarian Forest region of southeastern Germany, known for its rural landscape and historic castle ruins.
-
B.
Vienenburg
Vienenburg is a district of Goslar in Lower Saxony, Germany, known for its historic town center and proximity to the Harz Mountains.
-
C.
Betzdorf
Betzdorf is a commune in eastern Luxembourg known for its residential areas, railway facilities, and the presence of Betzdorf Castle.
-
D.
Hammelburg
Hammelburg is a historic town in northern Bavaria, Germany, known as one of the country’s oldest wine-growing communities.
-
E.
Bergheim
Bergheim is a municipality in the Austrian state of Salzburg, located just north of the city of Salzburg and known for its suburban character and proximity to the regional capital.
- 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: Biburg Triple: [Kelheim (district), containsMunicipality, Biburg]
Generated description
Biburg is a small municipality in the Lower Bavarian region of Germany, known for its rural character and historic monastery.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Biburg Target entity description: Biburg is a small municipality in the Lower Bavarian region of Germany, known for its rural character and historic monastery.
-
A.
Kollnburg
Kollnburg is a small municipality in the Bavarian Forest region of southeastern Germany, known for its rural landscape and historic castle ruins.
-
B.
Vienenburg
Vienenburg is a district of Goslar in Lower Saxony, Germany, known for its historic town center and proximity to the Harz Mountains.
-
C.
Betzdorf
Betzdorf is a commune in eastern Luxembourg known for its residential areas, railway facilities, and the presence of Betzdorf Castle.
-
D.
Hammelburg
Hammelburg is a historic town in northern Bavaria, Germany, known as one of the country’s oldest wine-growing communities.
-
E.
Bergheim
Bergheim is a municipality in the Austrian state of Salzburg, located just north of the city of Salzburg and known for its suburban character and proximity to the regional capital.
- 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_69d1af4770f88190b9952c4308c0c384 |
completed | April 5, 2026, 12:39 a.m. |
| NEDg | Description generation | batch_69d1b06d39b48190adaadbc81b4ffb9a |
completed | April 5, 2026, 12:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1b1511c7c8190ba7bc691ab2d3a13 |
completed | April 5, 2026, 12:48 a.m. |
Created at: March 30, 2026, 8:01 p.m.