Triple
T17574922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hochtaunuskreis |
E428038
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Waldsolms |
—
|
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: Waldsolms | Statement: [Hochtaunuskreis, contains, Waldsolms]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waldsolms Context triple: [Hochtaunuskreis, contains, Waldsolms]
-
A.
Waldsolms
chosen
Waldsolms is a small municipality in the German state of Hesse, situated in a rural area northwest of Frankfurt.
-
B.
Waldeck-Frankenberg
Waldeck-Frankenberg is a rural district in northern Hesse, Germany, known for its scenic landscapes, forests, and small historic towns.
-
C.
Mundolsheim
Mundolsheim is a suburban commune in northeastern France, located just north of Strasbourg in the Bas-Rhin department of the Grand Est region.
-
D.
Wallenfels
Wallenfels is a small town in northern Bavaria, Germany, known for its scenic location in the Franconian Forest region.
-
E.
Geispolsheim
Geispolsheim is a commune in northeastern France’s Grand Est region, situated near Strasbourg and known for its mix of traditional Alsatian character and modern industrial and commercial zones.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4593403648190836266dbdb6cfc9f |
completed | April 19, 2026, 4:25 a.m. |
Created at: April 10, 2026, 5:50 a.m.