Triple
T1970504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Starnberg |
E42787
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object |
Münsing
Münsing is a municipality in Bavaria, Germany, located near Lake Starnberg and known for its scenic rural landscape and proximity to the Alps.
|
E219467
|
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: Münsing | Statement: [Starnberg, hasNeighbouringMunicipality, Münsing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Münsing Context triple: [Starnberg, hasNeighbouringMunicipality, Münsing]
-
A.
Lüßbach
Lüßbach is a small river in Bavaria, Germany, that serves as one of the tributaries feeding into Lake Starnberg.
-
B.
Lahnstein
Lahnstein is a historic town in western Germany, located on the Rhine River in the state of Rhineland-Palatinate.
-
C.
Luterbach
Luterbach is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Aare River.
-
D.
Weidach
Weidach is a locality or district that forms part of the municipality of Blaustein in the state of Baden-Württemberg, Germany.
-
E.
Hilchenbach
Hilchenbach is a small town in the Siegerland region of North Rhine-Westphalia, Germany, known for its wooded hills and proximity to the Rothaar Mountains.
- 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: Münsing Triple: [Starnberg, hasNeighbouringMunicipality, Münsing]
Generated description
Münsing is a municipality in Bavaria, Germany, located near Lake Starnberg and known for its scenic rural landscape and proximity to the Alps.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Münsing Target entity description: Münsing is a municipality in Bavaria, Germany, located near Lake Starnberg and known for its scenic rural landscape and proximity to the Alps.
-
A.
Lüßbach
Lüßbach is a small river in Bavaria, Germany, that serves as one of the tributaries feeding into Lake Starnberg.
-
B.
Lahnstein
Lahnstein is a historic town in western Germany, located on the Rhine River in the state of Rhineland-Palatinate.
-
C.
Luterbach
Luterbach is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Aare River.
-
D.
Weidach
Weidach is a locality or district that forms part of the municipality of Blaustein in the state of Baden-Württemberg, Germany.
-
E.
Hilchenbach
Hilchenbach is a small town in the Siegerland region of North Rhine-Westphalia, Germany, known for its wooded hills and proximity to the Rothaar Mountains.
- 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_69a88711151c8190940b2572095059d7 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3d2836c8190a35cb6d8e2dd4bdf |
completed | March 7, 2026, 5:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfbd9a2dc81909f86fdfa9c646dd0 |
completed | March 8, 2026, 10:44 p.m. |
| NEDg | Description generation | batch_69adfc6e40f081909682afd84f4e9338 |
completed | March 8, 2026, 10:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adfd9fa4cc81909734a147626da4d1 |
completed | March 8, 2026, 10:52 p.m. |
Created at: March 4, 2026, 7:36 p.m.