Triple
T20029462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bergstraße district |
E495081
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Mörlenbach |
—
|
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: Mörlenbach | Statement: [Bergstraße district, contains, Mörlenbach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mörlenbach Context triple: [Bergstraße district, contains, Mörlenbach]
-
A.
Mörlenbach
chosen
Mörlenbach is a municipality in the Bergstraße district of Hesse, Germany, located in the Odenwald region.
-
B.
Miedelsbach
Miedelsbach is a village and district of the town of Schorndorf in the Rems-Murr district of Baden-Württemberg, Germany.
-
C.
Lüßbach
Lüßbach is a small river in Bavaria, Germany, that serves as one of the tributaries feeding into Lake Starnberg.
-
D.
Grävenwiesbach
Grävenwiesbach is a municipality in the Hochtaunus region of Hesse, Germany, known for its rural character and proximity to the Taunus mountains.
-
E.
Heroldsbach
Heroldsbach is a small municipality in the Upper Franconia region of Bavaria, Germany, known for its rural character and local religious pilgrimage site.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662908df081909a6c8ccf0dd90fff |
completed | April 20, 2026, 5:29 p.m. |
Created at: April 11, 2026, 3:36 p.m.