Triple
T19939159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bischofswerda |
E479256
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Löbau |
—
|
NE NERFINISHED |
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: Löbau | Statement: [Bischofswerda, hasTwinTown, Löbau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Löbau Context triple: [Bischofswerda, hasTwinTown, Löbau]
-
A.
Löbau
chosen
Löbau is a small town in the Free State of Saxony in eastern Germany, known for its historic architecture and location in the Lusatian Highlands.
-
B.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
C.
Faßberg
Faßberg is a municipality in Lower Saxony, Germany, known for its location in the Lüneburg Heath and its historical military airbase.
-
D.
Wuhletal
Wuhletal is a valley landscape in Berlin shaped by the course of the Wuhle river, featuring green spaces, walking paths, and recreational areas.
-
E.
Lülsfeld
Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a19d77c819088bce99c94568d0d |
completed | April 20, 2026, 4:53 p.m. |
Created at: April 10, 2026, 1:53 p.m.