Triple
T9540657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regen (district) |
E230146
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Arnbruck
Arnbruck is a small municipality in the Bavarian Forest region of southeastern Germany.
|
E808429
|
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: Arnbruck | Statement: [Regen (district), contains, Arnbruck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arnbruck Context triple: [Regen (district), contains, Arnbruck]
-
A.
Neuenegg
Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
-
B.
Aarburg
Aarburg is a historic Swiss town in the canton of Aargau, known for its prominent riverside fortress overlooking the Aare River.
-
C.
Attiswil
Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
-
D.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
-
E.
Waldegg
Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
- 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: Arnbruck Triple: [Regen (district), contains, Arnbruck]
Generated description
Arnbruck is a small municipality in the Bavarian Forest region of southeastern Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Arnbruck Target entity description: Arnbruck is a small municipality in the Bavarian Forest region of southeastern Germany.
-
A.
Neuenegg
Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
-
B.
Aarburg
Aarburg is a historic Swiss town in the canton of Aargau, known for its prominent riverside fortress overlooking the Aare River.
-
C.
Attiswil
Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
-
D.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
-
E.
Waldegg
Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
- 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_69d161355e2c819099c8e6b974f97608 |
completed | April 4, 2026, 7:06 p.m. |
| NEDg | Description generation | batch_69d16230a99481909d82d03babe6729a |
completed | April 4, 2026, 7:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d16321aba88190a7e8359dbaa5362b |
completed | April 4, 2026, 7:14 p.m. |
Created at: March 30, 2026, 8:01 p.m.