Based on my prior knowledge, I can analyze the relationship between the feature "n_p_ecg_p_07" (LBBB on ECG at admission) and the presence of chronic heart failure as a complication in the patient with myocardial infarction.

Since LBBB (Left Bundle Branch Block) is a conduction abnormality in which the electrical signals in the heart take a different pathway than usual, it can have implications for the heart's overall function. LBBB can be associated with various heart conditions, including chronic heart failure. Therefore, there is a likelihood that patients with LBBB at admission (n_p_ecg_p_07 = 'yes') may have an increased risk of chronic heart failure as a complication.

To generate the requested dictionary, I will assume that there are only two classes for the target variable (complications): 'no' and 'yes'. Here's the dictionary:

```json
{
	"no": ["no"],
	"yes": ["yes"]
}
```

In this case, since the feature is categorical, it can only take two values 'no' and 'yes'. Hence, there is no ambiguity in assigning the values to each target class.