Triple
T20029468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bergstraße district |
E495081
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Gorxheimertal |
—
|
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: Gorxheimertal | Statement: [Bergstraße district, contains, Gorxheimertal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gorxheimertal Context triple: [Bergstraße district, contains, Gorxheimertal]
-
A.
Gorxheimertal
chosen
Gorxheimertal is a small municipality in the Bergstraße district of Hesse, Germany, situated in a scenic valley on the edge of the Odenwald.
-
B.
Wehretal
Wehretal is a small municipality in the Werra-Meißner district of northern Hesse, Germany, known for its rural character and location in the Werra valley.
-
C.
Schnaudertal
Schnaudertal is a small municipality in the German state of Saxony-Anhalt that lies within the broader Leipzig metropolitan region.
-
D.
Löstertal
Löstertal is a locality within the town of Wadern in the Saarland region of Germany, known for its rural character and scenic surroundings.
-
E.
Schuttertal
Schuttertal is a rural municipality in southwestern Germany’s Baden-Württemberg region, situated within the Ortenaukreis district and known for its scenic valleys and Black Forest landscapes.
- 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.