nlp fucntion in python like so-

nlp = StanfordCoreNLP(host + ":" + port)
text = "Joshua Brown, 40, was killed in Florida in May when his Tesla failed to " \
       "differentiate between the side of a turning truck and the sky while " \
       "operating in autopilot mode."
output = nlp.annotate(
    text,
    properties={
        "outputFormat": "json",
        "annotators": "depparse,ner,entitymentions,sentiment"
    }
)
pprint(output)

and i get the output like so-

{
  'sentences': [
    {
      'basicDependencies': [
        {
          'dep': 'ROOT',
          'dependent': 7,
          'dependentGloss': 'killed',
          'governor': 0,
          'governorGloss': 'ROOT'
        },
        {
          'dep': 'compound',
          'dependent': 1,
          'dependentGloss': 'Joshua',
          'governor': 2,
          'governorGloss': 'Brown'
        },
        …
      ],
      'enhancedDependencies': [
        {
          'dep': 'ROOT',
          'dependent': 7,
          'dependentGloss': 'killed',
          'governor': 0,
          'governorGloss': 'ROOT'
        },
        {
          'dep': 'compound',
          'dependent': 1,
          'dependentGloss': 'Joshua',
          'governor': 2,
          'governorGloss': 'Brown'
        },

But I want to do the equivalent in Java, so I wrote a java method like-

public class NlpTest implements RequestHandler<Input,Output>{
    public static String text = "Multiple locations in Maharashtra linked to state transport minister Anil Parab were raided this morning by the Enforcement Directorate (ED) as part of a money-laundering probe relating to alleged irregularities in a land deal.";


    @Override
    public Output handleRequest(Input input, Context context) {


        String output="";
        try {
            System.out.println("entering method handleRequest");
            // load input from environment variable
//            String str = System.getenv("INPUT");

//            String str = input.getText();                            
String str="Multiple locations in Maharashtra linked to state transport minister Anil Parab were raided this morning by the Enforcement Directorate (ED) as part of a money-laundering probe relating to alleged irregularities in a land deal.";
            if (str.length() > 0)
                text = str;

            System.out.println("str = " + str);
            System.out.println("text = " + text);



            // Setup CoreNLP

            Properties props = new Properties();
            //props.setProperty("annotators", "tokenize, ssplit, pos, lemma, ner, parse, dcoref, tokensregex, sentiment");           //------>here
            props.setProperty("annotators", "depparse,ner,entitymentions,sentiment");
            props.setProperty("ner.additional.tokensregex.rules","src/main/java/custom.rules");

//            props.setProperty("coref.algorithm", "neural");
            props.setProperty("ner.useSUTime", "false");
            props.setProperty("outputFormat", "json");



            StanfordCoreNLP pipeline = new StanfordCoreNLP(props);


            CoreDocument doc = new CoreDocument(text);
            // annotate
            pipeline.annotate(doc);
            System.out.println("pipeline="+pipeline.toString());
            System.out.println("doc.entityMentions() = " + doc.entityMentions());
            // display tokens
            for (CoreLabel tok : doc.tokens()) {
                System.out.println(String.format("%s\t%d\t%d", tok.word(), tok.beginPosition(), tok.endPosition()));
            }
    

no matter what permutation/combinations i try to add in the line props.setProperty(“annotators” ,”tokenize, ssplit, pos, lemma, ner…”)
(mentioned “—->here” in the code)
I get error saying-

annotator "depparse" requires annotation "TextAnnotation". The usual requirements for this annotator are: tokenize,ssplit,pos

I just want to get the equivalent Python output..Please can anyone tell me where I am going wrong?
I am new to Stanford-core-NLP and any help is appreciated. Thanks!