Triple
T6632337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chernihiv |
E149955
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object | Memmingen |
E301302
|
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: Memmingen | Statement: [Chernihiv, hasSisterCity, Memmingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Memmingen Context triple: [Chernihiv, hasSisterCity, Memmingen]
-
A.
Memmingen
chosen
Memmingen is a historic town in the Bavarian region of Germany, known for its well-preserved medieval old town and role as a regional transport hub.
-
B.
Nucingen
Nucingen is a powerful and unscrupulous banker in Balzac’s La Comédie humaine, emblematic of the corrupt financial elite of 19th-century Paris.
-
C.
Schwanau
Schwanau is a municipality in southwestern Germany’s Baden-Württemberg region, situated near the Rhine River and the French border.
-
D.
Blaubeuren
Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
-
E.
Münklingen
Münklingen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
- 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6afc9138c81909d228ce4936d6b8b |
completed | March 27, 2026, 4:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7fa57aa9c819081d4ec62bf18d971 |
completed | March 28, 2026, 3:57 p.m. |
Created at: March 27, 2026, 1:59 p.m.