Triple
T15664276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke of Mecklenburg |
E376646
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Güstrow |
E400875
|
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: Güstrow | Statement: [Duke of Mecklenburg, hasCapital, Güstrow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Güstrow Context triple: [Duke of Mecklenburg, hasCapital, Güstrow]
-
A.
Güstrow
chosen
Güstrow is a historic town in northern Germany known for its Renaissance castle, brick Gothic cathedral, and association with sculptor Ernst Barlach.
-
B.
Fredericia
Fredericia is a Danish coastal town in Jutland known for its historic 17th-century fortress and well-preserved ramparts.
-
C.
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.
-
D.
Ratzeburg
Ratzeburg is a historic town in northern Germany known for its island old town and Romanesque cathedral, situated in the lake district of Schleswig-Holstein.
-
E.
Lauenburg
Lauenburg is a historic town in northern Germany situated on the banks of the Elbe 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f0f4df08190ad2c5d78e435d8eb |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff908dae948190bb6fb51e35aff5ac |
completed | May 9, 2026, 7:52 p.m. |
Created at: April 10, 2026, 4:16 a.m.