Generic Person Genderizer
Output
The person is clearly 'male'.
The person is clearly 'female'.
Can be either male or female. See malePercent
.
No gender could be computed, but better intelligence should be able to tell the gender. An example is a name input of which we have never heard before.
From the given data it is or seems impossible to tell the gender.
For example all terms are gender-inapplicable, or there are no names at all.
Thus this differs from NEUTRAL where something is clearly known to be neutral.
There are conflicting genders in the given data.
Example: "Mr Daniela Miller" (salutation vs. given name).
The input data must be manually reviewed. It is impossible and useless to make a guess (garbage in would only cause garbage out).
null
) then this may be specified (but does not have to be), 0-100, the remaining % are for female.