Triple
T1970503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Starnberg |
E42787
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object |
Gauting
Gauting is a municipality in the district of Starnberg in Bavaria, Germany, known for its residential character and proximity to Munich.
|
E372340
|
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: Gauting | Statement: [Starnberg, hasNeighbouringMunicipality, Gauting]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gauting Context triple: [Starnberg, hasNeighbouringMunicipality, Gauting]
-
A.
Forchheim
Forchheim is a town in Upper Franconia, Bavaria, Germany, known for its historic old town and location along major regional rail and road routes.
-
B.
Ingolstadt
Ingolstadt is a historic city in southern Germany known for its medieval architecture, university tradition, and role as a major hub of the automotive industry.
-
C.
Degendorf
Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
-
D.
Aschersleben
Aschersleben is a historic town in the German state of Saxony-Anhalt, known as one of the oldest documented cities in central Germany.
-
E.
Rosenheim
Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
- 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: Gauting Triple: [Starnberg, hasNeighbouringMunicipality, Gauting]
Generated description
Gauting is a municipality in the district of Starnberg in Bavaria, Germany, known for its residential character and proximity to Munich.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gauting Target entity description: Gauting is a municipality in the district of Starnberg in Bavaria, Germany, known for its residential character and proximity to Munich.
-
A.
Forchheim
Forchheim is a town in Upper Franconia, Bavaria, Germany, known for its historic old town and location along major regional rail and road routes.
-
B.
Ingolstadt
Ingolstadt is a historic city in southern Germany known for its medieval architecture, university tradition, and role as a major hub of the automotive industry.
-
C.
Degendorf
Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
-
D.
Aschersleben
Aschersleben is a historic town in the German state of Saxony-Anhalt, known as one of the oldest documented cities in central Germany.
-
E.
Rosenheim
Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
- 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_69b4029cfa148190baad6968cf6dad3a |
completed | March 13, 2026, 12:27 p.m. |
| NEDg | Description generation | batch_69b40da9e4808190a01d7305d4fdb7f3 |
completed | March 13, 2026, 1:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b42d8084c88190a2aae4a883d050a0 |
completed | March 13, 2026, 3:30 p.m. |
Created at: March 4, 2026, 7:36 p.m.