Triple
T7239011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lauenburg |
E155306
|
entity |
| Predicate | officialName |
P66
|
FINISHED |
| Object | Lauenburg/Elbe |
E155306
|
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: Lauenburg/Elbe | Statement: [Lauenburg, officialName, Lauenburg/Elbe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauenburg/Elbe Context triple: [Lauenburg, officialName, Lauenburg/Elbe]
-
A.
Teltow
Teltow is a town in the German state of Brandenburg, located just southwest of Berlin and known for its historical core and proximity to the capital.
-
B.
Aussig an der Elbe
Aussig an der Elbe is the German name for the Czech industrial and port city of Ústí nad Labem, located on the Elbe River in northern Bohemia.
-
C.
Lauenburg
chosen
Lauenburg is a historic town in northern Germany situated on the banks of the Elbe River.
-
D.
Müritz
Müritz is Germany’s largest lake entirely within the country, located in the Mecklenburg Lake District of northeastern Germany.
-
E.
Havelte
Havelte is a village in the Dutch province of Drenthe, known for its nearby prehistoric dolmens and scenic natural surroundings.
- 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_69c688143bfc81908d4176617735e601 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea37fa9081908e9c3abe49d151e5 |
completed | March 27, 2026, 8:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7cc3d75b48190916bf327396f2666 |
completed | March 28, 2026, 12:40 p.m. |
Created at: March 27, 2026, 2:55 p.m.