Triple
T13039959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kopřivnice |
E327165
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Zwönitz |
E80007
|
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: Zwönitz | Statement: [Kopřivnice, hasTwinTown, Zwönitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zwönitz Context triple: [Kopřivnice, hasTwinTown, Zwönitz]
-
A.
Zwönitz
chosen
Zwönitz is a river in Saxony, Germany, that serves as one of the headstreams of the Chemnitz River.
-
B.
Kühnitzsch
Kühnitzsch is a village-level subdivision of the town of Wurzen in the German state of Saxony.
-
C.
Wülknitz
Wülknitz is a small municipality in the German state of Saxony that forms part of the broader Leipzig metropolitan area.
-
D.
Wanzleben
Wanzleben is a small town in the German state of Saxony-Anhalt, historically part of the former East German administrative district of Magdeburg.
-
E.
Brünnlitz
Brünnlitz is a village in the Czech Republic best known as the location of Oskar Schindler’s wartime factory where he employed and saved Jewish workers during the Holocaust.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d9804d8e3081909584c93df099859a |
completed | April 10, 2026, 10:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7265d09d881909c21423d93af39cd |
completed | May 3, 2026, 10:41 a.m. |
Created at: April 9, 2026, 8:55 p.m.