Triple
T1890380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Starnberger See |
E41860
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Town of Starnberg |
E42787
|
NE FINISHED |
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: Town of Starnberg | Statement: [Starnberger See, namedAfter, Town of Starnberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Town of Starnberg Context triple: [Starnberger See, namedAfter, Town of 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.
Oberkirch
Oberkirch is a town in the Ortenau district of Baden-Württemberg in southwestern Germany, known for its wine production and picturesque location at the edge of the Black Forest.
-
C.
Bad Reichenhall
Bad Reichenhall is a Bavarian spa town in southeastern Germany, renowned for its alpine setting and historic salt production.
-
D.
Oberwallenstadt
Oberwallenstadt is a village and district of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
-
E.
Schwandorf
Schwandorf is a town in the Upper Palatinate region of Bavaria, Germany, known as a local administrative and commercial center on the Naab River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb14475448190b291ada3454bf98b |
completed | March 7, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69addf68a8d48190a3360557def67692 |
completed | March 8, 2026, 8:43 p.m. |
Created at: March 4, 2026, 7:34 p.m.