Triple
T521255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hesse-Kassel |
E10821
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Kurhessen |
E10821
|
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: Kurhessen | Statement: [Hesse-Kassel, alsoKnownAs, Kurhessen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kurhessen Context triple: [Hesse-Kassel, alsoKnownAs, Kurhessen]
-
A.
Hesse
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.
Hesse-Kassel
chosen
Hesse-Kassel was a German principality known for supplying large numbers of Hessian mercenary troops to fight alongside the British during the American Revolutionary War.
-
C.
Thuringia
Thuringia is a federal state in central Germany known for its forested landscapes, historic cities like Weimar and Erfurt, and its rich cultural and intellectual heritage.
-
D.
Baden-Württemberg
Baden-Württemberg is a federal state in southwest Germany known for its strong economy, automotive industry, and cities like Stuttgart, Heidelberg, and Freiburg.
-
E.
Franconia
Franconia is a suburban community in Fairfax County, Northern Virginia, known for its residential neighborhoods and proximity to Washington, D.C.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1a1817c8190a6cc8f423071d3ad |
completed | Feb. 28, 2026, 1:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5914232c481909a39cd3373e3c6c9 |
completed | March 2, 2026, 1:31 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.