Triple
T20206358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bodenseekreis |
E493361
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Langenargen
Langenargen is a lakeside municipality in southern Germany situated on the shore of Lake Constance, known for its scenic waterfront and historic Montfort Castle.
|
E1420031
|
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: Langenargen | Statement: [Bodenseekreis, hasMunicipality, Langenargen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Langenargen Context triple: [Bodenseekreis, hasMunicipality, Langenargen]
-
A.
Aarburg
Aarburg is a historic Swiss town in the canton of Aargau, known for its prominent riverside fortress overlooking the Aare River.
-
B.
Eriswil
Eriswil is a rural Swiss village and municipality located in the hilly Emmental region of the canton of Bern.
-
C.
Rüegsau
Rüegsau is a rural municipality in the Emmental region of the canton of Bern in Switzerland, known for its agricultural landscape and traditional Swiss village character.
-
D.
Waldegg
Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
-
E.
Eggenwil
Eggenwil is a small municipality in the canton of Aargau in northern Switzerland, situated near the Reuss River and characterized by its rural, village-like setting.
- 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: Langenargen Triple: [Bodenseekreis, hasMunicipality, Langenargen]
Generated description
Langenargen is a lakeside municipality in southern Germany situated on the shore of Lake Constance, known for its scenic waterfront and historic Montfort Castle.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Langenargen Target entity description: Langenargen is a lakeside municipality in southern Germany situated on the shore of Lake Constance, known for its scenic waterfront and historic Montfort Castle.
-
A.
Aarburg
Aarburg is a historic Swiss town in the canton of Aargau, known for its prominent riverside fortress overlooking the Aare River.
-
B.
Eriswil
Eriswil is a rural Swiss village and municipality located in the hilly Emmental region of the canton of Bern.
-
C.
Rüegsau
Rüegsau is a rural municipality in the Emmental region of the canton of Bern in Switzerland, known for its agricultural landscape and traditional Swiss village character.
-
D.
Waldegg
Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
-
E.
Eggenwil
Eggenwil is a small municipality in the canton of Aargau in northern Switzerland, situated near the Reuss River and characterized by its rural, village-like setting.
- 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_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66d922ebc8190ae012da8ceba74dd |
completed | April 20, 2026, 6:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08551a0dd8819092042277a39e643a |
completed | May 16, 2026, 11:29 a.m. |
| NEDg | Description generation | batch_6a0855ea027481908eebd5cff8ac97fb |
completed | May 16, 2026, 11:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08568fa1748190b4e2c21fc3ec0b63 |
completed | May 16, 2026, 11:35 a.m. |
Created at: April 11, 2026, 11:38 p.m.