Triple
T13110542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greiz |
E310957
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object | Berga/Elster |
E382605
|
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: Berga/Elster | Statement: [Greiz, hasNeighbouringMunicipality, Berga/Elster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berga/Elster Context triple: [Greiz, hasNeighbouringMunicipality, Berga/Elster]
-
A.
Berga an der Elster
chosen
Berga an der Elster is a small town in Thuringia, Germany, historically known for hosting a Nazi concentration camp subcamp during World War II.
-
B.
Falkenberg/Elster
Falkenberg/Elster is a town in the state of Brandenburg in eastern Germany, known historically as a regional railway junction.
-
C.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
D.
Günsberg
Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
-
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 (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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9817e4f408190b77c198b4157d77a |
completed | April 10, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e27d8110819087ade3537f867ae0 |
completed | May 3, 2026, 5:51 a.m. |
Created at: April 9, 2026, 9:05 p.m.