Triple
T636950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kassel Huskies |
E16642
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | North 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: North Hesse | Statement: [Kassel Huskies, region, North Hesse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: North Hesse Context triple: [Kassel Huskies, region, North 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.
Sachse
Sachse is a suburban city in the Dallas–Fort Worth metropolitan area of northeastern Texas.
-
C.
Franconia
Franconia is a suburban community in Fairfax County, Northern Virginia, known for its residential neighborhoods and proximity to Washington, D.C.
-
D.
Upper Palatinate
Upper Palatinate is a historical region in eastern Bavaria, Germany, known for its forests, rivers, and medieval towns near the Czech border.
-
E.
Emsland
Emsland is a rural region in western Germany known for its agriculture, peatlands, and location along the River Ems near the Dutch border.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ee7fdbc8190858e42bb1bfdb3ff |
completed | March 1, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a67eeff434819090fb550b6bf07d86 |
completed | March 3, 2026, 6:25 a.m. |
Created at: March 1, 2026, 7:35 p.m.