The way I learned it, a tensor is a multilinear map:
$T:\underbrace{V \times \cdots \times V}_{n\ copies} \times \underbrace{V^{\ast} \times \cdots \times V^{\ast}}_{m\ copies} \to F$
We can, by the universality of the tensor product, regard $T$ as an element of:
$\underbrace{V^{\ast} \otimes \cdots \otimes V^{\ast}}_{n\ copies} \otimes \underbrace{V \otimes \cdots \otimes V}_{m\ copies}$
(here, we are implicitly identifying $V$ with $V^{\ast\ast}$).
In this case, $m = n = 1$, which makes our tensor particularly easy to understand. In this case, we have that any such tensor is a linear combination of elementary tensors of basis covectors and vectors. So it suffices to determine what:
$e^j \otimes e_i (v,u^{\ast})$ is, for any two vectors $u,v \in V$.
Typically, $\{e_1,\dots,e_n\}$ is the standard (Euclidean) basis for $F^n$, and $\{e^1,\dots,e^n\}$ is the dual basis; that is, the linear functionals:
$\displaystyle e^j(v) = e^j\left(\sum_{i = 1}^n v^ie_i \right) = v^j$
(the linear functional that returns the $j$-th coordinate of $v$ in the standard basis).
It is typical to regard $e_i$ as an $n \times 1$ (column) matrix, and $e^j$ as a $1 \times n$ (row) matrix, in which case their tensor product is given by their Kronecker product, the $n \times n$ matrix (written below in block form):
$\begin{bmatrix}0e_i&\dots&1e_i&\dots&0e_n \end{bmatrix}$
$= E_{ij}$, which has a 1 in the $i,j$-th entry, and 0's elsewhere. That is:
$e^j \otimes e_i (v,u^{\ast}) = u^TE_{ij}v = (u^{\ast})_iv^j$
(I hope I have my indices correct...I get these backwards a lot).
In this example, we have $V = F^3$ (as near as I can surmise), with:
$v = (1,5,4)$ (in the basis of $\{e_1,e_2,e_3\}$ and
$f = (1,1,1)^{\ast}$ (in the dual basis), so that:
$e^1 \otimes e_2(v,f)$ returns the product of the first coordinate of $v$ with the second coordinate of $f$.
(Tensor products become very unwieldy to explictly compute once m and n start to get larger than 2, as the number of operations to do gets rather large).