Triple
T17985353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andechs |
E430215
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Starnberg |
—
|
NE NERFINISHED |
How this triple was built (2 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: Starnberg | Statement: [Andechs, hasNearbyCity, Starnberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Starnberg Context triple: [Andechs, hasNearbyCity, Starnberg]
-
A.
Starnberg
chosen
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
-
B.
Steinhausen
Steinhausen is a municipality in the canton of Zug in central Switzerland, known for its residential character and proximity to the city of Zug.
-
C.
Regenstauf
Regenstauf is a market town in the Upper Palatinate region of Bavaria, Germany, situated north of the city of Regensburg along the river Regen.
-
D.
Planegg
Planegg is a municipality in the district of Munich in Bavaria, Germany, known for its scenic location along the Würm River and its proximity to the city of Munich.
-
E.
Stollberg
Stollberg is a historic town in Saxony, Germany, known for its role in the Ore Mountains mining region and its traditional mining heritage.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29a27b081909a128a6b978eabf8 |
completed | April 19, 2026, 10:46 a.m. |
Created at: April 10, 2026, 10:23 a.m.