Triple
T8581165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Kassel |
E203181
|
entity |
| Predicate | state |
P87
|
FINISHED |
| Object | Hesse |
E14304
|
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: Hesse | Statement: [University of Kassel, state, Hesse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hesse Context triple: [University of Kassel, state, Hesse]
-
A.
Hesse
chosen
Hesse is a federal state in central Germany known for its financial hub Frankfurt am Main and its mix of urban centers, forests, and historic towns.
-
B.
South Hesse
South Hesse is a region in the southern part of the German state of Hesse that includes major urban and economic centers such as Darmstadt and the Rhine-Main area.
-
C.
Kurhessen
Kurhessen was a historical region in central Germany that formed the core territory of the Electorate of Hesse (Hesse-Kassel) within the Holy Roman Empire and later German states.
-
D.
Greater Hesse
Greater Hesse was a post–World War II administrative region in western Germany established by the U.S. occupation authorities, which later formed the core of the modern state of Hesse.
-
E.
Rübeland
Rübeland is a village in the Harz Mountains of central Germany, known for its show caves and scenic natural surroundings.
- 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_69ca8329bb7c8190a63c643730839103 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbeb1bbbd8819082670286a711826d |
completed | March 31, 2026, 3:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea89550f481908a7ed45303b71731 |
completed | April 2, 2026, 5:34 p.m. |
Created at: March 30, 2026, 6:22 p.m.