Triple
T9439514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lahn-Dill-Kreis |
E227605
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Solms |
E379219
|
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: Solms | Statement: [Lahn-Dill-Kreis, hasMunicipality, Solms]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Solms Context triple: [Lahn-Dill-Kreis, hasMunicipality, Solms]
-
A.
Solms-Braunfels
chosen
Solms-Braunfels was a German noble house from the region of Hesse, historically associated with various counts and princes in the Holy Roman Empire.
-
B.
Gerhardt
Gerhardt is a German-origin surname borne by various individuals and families, often associated with Central European heritage.
-
C.
Hohneck
Hohneck is one of the highest peaks in the Vosges Mountains of northeastern France, known for its panoramic views and popular hiking and skiing opportunities.
-
D.
Meyer-Lübke
Meyer-Lübke is the surname of Wilhelm Meyer-Lübke, a prominent Swiss linguist known for his influential work in Romance philology.
-
E.
Böhme
The Böhme is a river in Lower Saxony, Germany, known for flowing through the Lüneburg Heath region before joining the Aller.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ee1c8c48190a2ae8673eee07e9a |
completed | April 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1105909248190b3e02a1aa5f06b11 |
completed | April 4, 2026, 1:21 p.m. |
Created at: March 30, 2026, 7:50 p.m.