stanford nlp - Check for words in input text from words collection -

i have collection of noun phrases around 10,000 words. want check every new input text data these np collection , extract sentences contains of these np. don't want run loops every word because makes code dead slow. using java , stanford corenlp.

a quick , easy way use regexner identify examples of in dictionary, , check non "o" ner tags in sentence.

package edu.stanford.nlp.examples;  import edu.stanford.nlp.ling.*; import edu.stanford.nlp.pipeline.*; import edu.stanford.nlp.util.*; import java.util.*; import java.util.stream.collectors;  public class findsentenceswithphrase {    public static boolean checkfornamedentity(coremap sentence) {     (corelabel token : sentence.get(coreannotations.tokensannotation.class)) {       if (token.ner() != null && !token.ner().equals("o")) {         return true;       }     }     return false;   }    public static void main(string[] args) {     properties props = new properties();     props.setproperty("annotators", "tokenize,ssplit,pos,lemma,regexner");     props.setproperty("regexner.mapping", "phrases.rules");     stanfordcorenlp pipeline = new stanfordcorenlp(props);     string exampletext = "this sentence contains phrase \"ice cream\"." +         "this sentence not of interest.  sentences contains pizza.";     annotation ann = new annotation(exampletext);     pipeline.annotate(ann);     (coremap sentence : ann.get(coreannotations.sentencesannotation.class)) {       if (checkfornamedentity(sentence)) {         system.out.println("---");         system.out.println(sentence.get(coreannotations.tokensannotation.class).             stream().map(token -> token.word()).collect(collectors.joining(" ")));       }     }   } } 

the file "phrases.rules" should this:

ice cream       phrase_of_interest      misc    1 pizza   phrase_of_interest      misc    1