No, your formula isn't correct. I don't know how you came to it, so I don't know what's wrong with your intuition.
You can check whether your formula makes sense with dimensional observation — it's the same kind of reasoning that helps a lot in physics. Write all numbers with their units:
- entropy rate = 1.5 bit/character
- random key size = 128 bits
- passphrase length = X characters
- information content per character in a 26-character alphabet = log2(26) bits/character = 4.7 bit/character
Your formula: $\dfrac{128\text{ bit}}{4.7\text{ bit/character}} \times 1.5\text{ bit/character} \approx 40.85\color{red}{\text{ bit}}$
We expected a number of characters, so something is wrong here.
In order to achieve the strength of a 128-bit random key, we need a total entropy of 128 bits for the passphrase. It's a simple proportionality rule:
$$
\text{entropy per character} =
\frac{\text{total entropy}}{\text{number of characters}}
$$
so
$$
X\text{ characters} = \frac{\text{total entropy}}{\text{entropy per character}}
= \frac{128\text{ bit}}{1.5\text{ bit/character}}
\approx 85.3\text{ character}
$$
Sanity check: the passphrase length turns up as a number of characters. Since the number of characters has to be an integer, it needs to be at least 86 characters long.
The size of the alphabet is irrelevant here because the passphrase isn't chosen randomly over all possible sequences of letters. “Passphrase” implies that it is a sentence fragment in a human language, or close enough. 1.5 bit/letter is a common estimate for the entropy per character for English: the number of English sentences of length $L$ is approximately $2^{1.5·L}$, so if you pick one at random, you have a $1/(2^{1.5})^L$ chance of being right.