Triple
T8857637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hammersbach |
E210797
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Höllental |
E210797
|
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: Höllental | Statement: [Hammersbach, flowsThrough, Höllental]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Höllental Context triple: [Hammersbach, flowsThrough, Höllental]
-
A.
Höllental
chosen
Höllental is a steep, scenic alpine valley in the Bavarian Alps known for its challenging route up to Germany’s highest peak, the Zugspitze.
-
B.
Gorxheimertal
Gorxheimertal is a small municipality in the Bergstraße district of Hesse, Germany, situated in a scenic valley on the edge of the Odenwald.
-
C.
Klostertal
Klostertal is a scenic alpine valley in the Austrian state of Vorarlberg, known for its mountain landscapes, ski areas, and access to the Arlberg 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 (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_69ca838bbddc8190ab546d737e5d350f |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60e3b62c8190bf779e7e1db767f6 |
completed | April 1, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc1c3c6c08190b51ea5e9cf7085e9 |
completed | April 3, 2026, 1:33 p.m. |
Created at: March 30, 2026, 6:50 p.m.