Triple
T9208389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District of Weilheim-Schongau |
E221046
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Antdorf
Antdorf is a small rural municipality in Upper Bavaria, Germany, known for its traditional Bavarian character and scenic Alpine foothill landscape.
|
E790187
|
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: Antdorf | Statement: [District of Weilheim-Schongau, containsMunicipality, Antdorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Antdorf Context triple: [District of Weilheim-Schongau, containsMunicipality, Antdorf]
-
A.
Attiswil
Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
-
B.
Waldegg
Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
-
C.
Burgdorf
Burgdorf is a historic Swiss town in the canton of Bern, known for its medieval castle and role as a regional economic and cultural center.
-
D.
Andelfingen
Andelfingen is a municipality and regional center in the canton of Zürich in northern Switzerland, known for its rural character and vineyards along the Thur River.
-
E.
Nideggen
Nideggen is a historic town in North Rhine-Westphalia, Germany, known for its medieval castle and scenic location in the Eifel 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: Antdorf Triple: [District of Weilheim-Schongau, containsMunicipality, Antdorf]
Generated description
Antdorf is a small rural municipality in Upper Bavaria, Germany, known for its traditional Bavarian character and scenic Alpine foothill landscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Antdorf Target entity description: Antdorf is a small rural municipality in Upper Bavaria, Germany, known for its traditional Bavarian character and scenic Alpine foothill landscape.
-
A.
Attiswil
Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
-
B.
Waldegg
Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
-
C.
Burgdorf
Burgdorf is a historic Swiss town in the canton of Bern, known for its medieval castle and role as a regional economic and cultural center.
-
D.
Andelfingen
Andelfingen is a municipality and regional center in the canton of Zürich in northern Switzerland, known for its rural character and vineyards along the Thur River.
-
E.
Nideggen
Nideggen is a historic town in North Rhine-Westphalia, Germany, known for its medieval castle and scenic location in the Eifel 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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd9b217008190a0ab4971dd4a8899 |
completed | April 1, 2026, 8:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0b1adc2508190b8a24510ee61f092 |
completed | April 4, 2026, 6:37 a.m. |
| NEDg | Description generation | batch_69d0b2b9fbf4819083e594d676323c65 |
completed | April 4, 2026, 6:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0b343a040819098620e2e3c451b39 |
completed | April 4, 2026, 6:44 a.m. |
Created at: March 30, 2026, 7:26 p.m.