diff --git a/NDTensors/src/lib/GradedAxes/src/gradedunitrange.jl b/NDTensors/src/lib/GradedAxes/src/gradedunitrange.jl
index 5f23a7f351..57e9420d88 100644
--- a/NDTensors/src/lib/GradedAxes/src/gradedunitrange.jl
+++ b/NDTensors/src/lib/GradedAxes/src/gradedunitrange.jl
@@ -55,7 +55,7 @@ end
 # error with a conversion method in Base.
 using BlockArrays: BlockSlice
 function Base.UnitRange{T}(
-  a::BlockSlice{<:Any,<:LabelledInteger{T},<:GradedUnitRange{<:LabelledInteger{T}}}
+  a::BlockSlice{<:Any,<:LabelledInteger{T},<:AbstractUnitRange{<:LabelledInteger{T}}}
 ) where {T<:Integer}
   return UnitRange{T}(a.indices)
 end
diff --git a/NDTensors/src/lib/GradedAxes/src/unitrangedual.jl b/NDTensors/src/lib/GradedAxes/src/unitrangedual.jl
index 8b66e33850..1ef1c62a51 100644
--- a/NDTensors/src/lib/GradedAxes/src/unitrangedual.jl
+++ b/NDTensors/src/lib/GradedAxes/src/unitrangedual.jl
@@ -108,3 +108,12 @@ function Base.OrdinalRange{Int,Int}(
   # return Int.(r)
   return unlabel(nondual(r))
 end
+
+# This is only needed in certain Julia versions below 1.10
+# (for example Julia 1.6).
+# TODO: Delete this once we drop Julia 1.6 support.
+# The type constraint `T<:Integer` is needed to avoid an ambiguity
+# error with a conversion method in Base.
+function Base.UnitRange{T}(a::UnitRangeDual{<:LabelledInteger{T}}) where {T<:Integer}
+  return UnitRange(nondual(a))
+end