code: package zemberek.morphology.ambiguity;
  
  import com.google.common.collect.HashMultimap;
  import com.google.common.collect.Multimap;
  import java.io.IOException;
  import java.nio.file.Files;
  import java.nio.file.Path;
  import java.nio.file.Paths;
  import java.util.ArrayList;
  import java.util.LinkedHashSet;
  import java.util.List;
  import java.util.stream.Collectors;
  import zemberek.core.logging.Log;
  import zemberek.tokenization.TurkishTokenizer;
  
  public class AmbigiousContextExtractor extends AmbiguityScriptsBase {
  
    public AmbigiousContextExtractor() throws IOException {
      super();
      acceptWordPredicates.add(maxAnalysisCount(10));
      acceptWordPredicates.add(hasAnalysis());
      ignoreSentencePredicates.add(contains("\""));
      ignoreSentencePredicates.add(contains("…"));
      ignoreSentencePredicates.add(probablyNotTurkish());
      ignoreSentencePredicates.add(tooLongSentence(25));
    }
  
    public static void main(String[] args) throws IOException {
      //Path p = Paths.get("/media/aaa/Data/corpora/final/www.aljazeera.com.tr");
      //Path p = Paths.get("/home/ahmetaa/data/zemberek/data/corpora/www.aljazeera.com.tr");
      Path p = Paths.get("/home/ahmetaa/data/zemberek/data/corpora/open-subtitles");
      //Path p = Paths.get("/home/ahmetaa/data/zemberek/data/corpora/wowturkey.com");
      //Path p = Paths.get("/media/aaa/Data/corpora/final/open-subtitles");
      //Path p = Paths.get("/media/aaa/Data/corpora/final/wowturkey.com");
      Path outRoot = Paths.get("data/ambiguity");
      Files.createDirectories(outRoot);
  
      List<String> words = Files.readAllLines(outRoot.resolve("zemberek-ambigious-words.txt"));
  
      AmbigiousContextExtractor e = new AmbigiousContextExtractor();
  
      List<Path> files = Files.walk(p, 1).filter(s -> s.toFile().isFile())
          .collect(Collectors.toList());
  
      Multimap<String, String> result = HashMultimap.create();
  
      for (Path file : files) {
        Log.info("Processing %s", file);
        LinkedHashSet<String> sentences = e.getSentences(file);
        //for (int i = 0; i < 10; i++) {
          //String s = words.get(i);
          String s = "kazan";
          LinkedHashSet<String> partials = e.extract(s, 2, 200, sentences);
          System.out.println(s);
          for (String partial : partials) {
            System.out.println(partial);
          }
        //}
        //break;
      }
  
    }
  
    public LinkedHashSet<String> extract(String word, int contextSize, int sentenceCount,
        LinkedHashSet<String> sentences) {
  
      LinkedHashSet<String> partials = new LinkedHashSet<>();
      List<List<String>> group = group(new ArrayList<>(sentences), 5000);
  
      for (List<String> lines : group) {
        LinkedHashSet<String> toProcess = getAccpetableSentences(lines);
        for (String sentence : toProcess) {
          if (sentence.contains(word)) {
            List<String> words = TurkishTokenizer.DEFAULT.tokenizeToStrings(sentence);
            for (int i = 0; i < words.size(); i++) {
              if (words.get(i).equals(word)) {
                int start = i - contextSize < 0 ? 0 : i - contextSize;
                int end = i + contextSize >= words.size() ? words.size() : i + contextSize + 1;
                String s = String.join(" ", words.subList(start, end));
                partials.add(s);
                System.out.println(s);
                if (partials.size() > sentenceCount) {
                  return partials;
                }
                break;
              }
            }
          }
        }
      }
      return partials;
    }
  
  
  }
  