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.

```

#### 2. Add Suggestion Documents

```java
import org.codelibs.fess.suggest.entity.SuggestItem;

// Create suggestion item with text, readings, and metadata
String[][] readings = new String[2][];
readings[0] = new String[]{"kensaku", "engine"};
readings[1] = new String[]{"search", "injin"};

String[] tags = new String[]{"technology", "search"};
String[] roles = new String[]{"admin", "user"};

 *
 * <p>
 * This class implements the {@link ReadingConverter} interface and provides a method to convert a given
 * Katakana string into a list of possible Alphabet readings. It uses a predefined mapping of Katakana
 * characters to their Alphabet equivalents, handling both single and double Katakana character combinations.
 * </p>
 *
 * <p>

        final Map<String, Object> secondLine = new HashMap<>();

        secondLine.put("text", item.getText());

        // reading
        final String[][] readings = item.getReadings();
        for (int i = 0; i < readings.length; i++) {
            secondLine.put("reading_" + i, readings[i]);
        }

        secondLine.put("fields", item.getFields());
        secondLine.put("queryFreq", item.getQueryFreq());

 * 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 {
    /**

            super(term, position, startOffset, endOffset, positionIncrement, type, attributes);
        }

        public String getReading() {
            return reading;
        }

        public void setReading(String reading) {
            this.reading = reading;
        }
    }

 * <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>

    }

    @Test
    public void testCreateBulkLine() {
        // Test creating bulk line for indexing
        SuggestItem item = new SuggestItem(new String[] { "test text" }, new String[][] { { "reading1" }, { "reading2" } },
                new String[] { "field1", "field2" }, 10, // queryFreq
                5, // docFreq
                2.0f, // userBoost

                    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) {

    }

    /**
     * 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.