*
     * @param elevateWord the elevate word
     * @param boost the boost value
     * @param readings the list of readings
     * @param fields the list of fields
     * @param tags the list of tags
     * @param roles the list of roles
     */
    public ElevateWord(final String elevateWord, final float boost, final List<String> readings, final List<String> fields,
            final List<String> tags, final List<String> roles) {

import java.io.IOException;
import java.util.List;

/**
 * Interface for converting text into its reading form.
 */
public interface ReadingConverter {

    /**
     * Returns the maximum number of readings.
     *
     * @return the maximum number of readings, default is 10.
     */
    default int getMaxReadingNum() {
        return 10;
    }

    /**

 */
public interface ContentsParser {
    /**
     * Parses the given search words and creates a SuggestItem.
     *
     * @param words the array of search words
     * @param readings the array of readings corresponding to the search words
     * @param fields the array of fields associated with the search words
     * @param tags the array of tags associated with the search words

 * <li>{@link #ANALYZER_SETTINGS_FIELD_NAME} - The analyzer settings field name.</li>
 * <li>{@link #ANALYZER_SETTINGS_READING_ANALYZER} - The reading analyzer settings field.</li>
 * <li>{@link #ANALYZER_SETTINGS_READING_TERM_ANALYZER} - The reading term analyzer settings field.</li>
 * <li>{@link #ANALYZER_SETTINGS_NORMALIZE_ANALYZER} - The normalize analyzer settings field.</li>

            final List<String> roles = (List<String>) sourceArray[i].get(ELEVATE_WORD_ROLES);
            if (elevateWord != null && boost != null && readings != null && fields != null) {
                elevateWords[i] =
                        new ElevateWord(elevateWord.toString(), Float.parseFloat(boost.toString()), readings, fields, tags, roles);
            }
        }
        return elevateWords;
    }

    /**
     * Add an elevate word.

                    final String term = termTokenList.get(i).getTerm();
                    String reading = readingTokenList.get(i).getTerm();
                    if (Strings.isNullOrEmpty(reading)) {
                        reading = term;
                    }
                    reading = transliterator.transliterate(reading);

                    final int pos = text.indexOf(term, offset);
                    if (pos > 0) {

                    continue;
                }

                String reading = getReadingFromAttribute(stream);
                if (Strings.isNullOrEmpty(reading)) {
                    reading = transliterator.transliterate(att.toString());
                }
                kanaBuf.append(reading);
                offset += term.length();
            }
        }

    }

    /**
     * Sets the reading converter.
     * @param readingConverter The reading converter.
     * @return This builder instance.
     */
    public SuggesterBuilder readingConverter(final ReadingConverter readingConverter) {
        this.readingConverter = readingConverter;
        return this;
    }

    /**
     * Sets the contents reading converter.

 * A chain of {@link ReadingConverter} implementations that applies each converter in sequence to generate possible reading variations of a given text.
 * It maintains a list of ReadingConverter instances and iterates through them, applying each converter to the input text and accumulating the results.
 * The chain stops processing when the maximum number of readings is reached.
 */
public class ReadingConverterChain implements ReadingConverter {
    /**

    /**
     * Analyzes the given text and returns a list of tokens along with their readings.
     *
     * @param text the text to analyze
     * @param field the field associated with the text
     * @param lang the language of the text
     * @return a list of analyzed tokens with their readings
     */
    List<AnalyzeToken> analyzeAndReading(String text, String field, String lang);