Hmm this example is interesting:<p><pre><code>    nlp.person(&quot;Tony Hawk&quot;).pronoun();
    &#x2F;&#x2F; &#x27;he&#x27;
</code></pre>
I was curious how it handled gender neutral names, since being able to identify gender from a name would be an awesome UX win. I tried a variety of different names, and for gender neutral names (ie &quot;Alex&quot; or &quot;Taylor&quot;), it always picked &quot;he&quot;. If it doesn&#x27;t recognize the name (ie &quot;Alexa&quot;), it returns &quot;they&quot;. Unfortunately, it only recognizes very standard American names. Anything remotely ethnic (ie &quot;Anjali&quot;) or slightly uncommon (ie &quot;Nate&quot;) results in a &quot;they&quot;.<p>Not picking on the library, since this would be an impossible task even for a human, but it seems odd to have used pronoun identification as one of the headline examples.<p>Anyway, awesome library overall. This could pair well with a dedicated date parsing library like Sherlock[1] to create some pretty cool conversational UI elements.<p>1: <a href="https:&#x2F;&#x2F;github.com&#x2F;neilgupta&#x2F;sherlock" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;neilgupta&#x2F;sherlock</a>