Triple
T2287245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Kleinen |
E51420
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Wismar |
E125507
|
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: Wismar | Statement: [Bad Kleinen, hasNearbyCity, Wismar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wismar Context triple: [Bad Kleinen, hasNearbyCity, Wismar]
-
A.
Wismar
chosen
Wismar is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval architecture and UNESCO-listed old town.
-
B.
Rostock
Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
-
C.
Lübeck
Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
-
D.
Schwerin
Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
-
E.
Neubrandenburg
Neubrandenburg is a historic city in northeastern Germany known for its well-preserved medieval brick Gothic architecture and distinctive city wall with multiple gate towers.
- 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_69a88b09c644819090b503456d96bf70 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc24868048190940512fd6449d99e |
completed | March 7, 2026, 6:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01d0915148190b77b8a30fa3f796d |
completed | March 10, 2026, 1:30 p.m. |
Created at: March 4, 2026, 7:48 p.m.