document.accept(new AbstractVisitor() {
            @Override
            public void visit(final Heading heading) {
                final StringBuilder headingText = new StringBuilder();
                Node child = heading.getFirstChild();
                while (child != null) {
                    if (child instanceof Text) {

 * <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>

 * <li>{@link #langFieldName} - Language field name.
 * <li>{@link #badWords} - List of bad words.
 * <li>{@link #parallel} - Flag for parallel processing.
 * <li>{@link #readingConverter} - Reading converter.
 * <li>{@link #contentsReadingConverter} - Contents reading converter.
 * <li>{@link #normalizer} - Normalizer.
 * <li>{@link #analyzer} - Suggest analyzer.
 * <li>{@link #contentsParser} - Contents parser.

                    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) {

     * @param langFieldName The name of the field that contains language information.
     * @param readingConverter The converter to use for reading fields.
     * @param contentsReadingConverter The converter to use for reading content fields.
     * @param normalizer The normalizer to use for normalizing field values.
     * @param analyzer The analyzer to use for analyzing field values.

                        final String reading = readingList.get(readingCount);
                        if (i + 1 == queries.length && prefixQuery) {
                            readingQueryBuilder.should(QueryBuilders.prefixQuery(fieldName, reading));
                        } else {
                            readingQueryBuilder.should(QueryBuilders.termQuery(fieldName, reading));
                        }
                    }

            entry.updateState(newState);

            // Flush any cached data if losing write cache
            if (Smb2LeaseState.hasWriteCaching(oldState) && !Smb2LeaseState.hasWriteCaching(newState)) {
                flushCachedWrites(entry.getPath());
            }

            // Invalidate cached data if losing read cache

    public String token;

    /** Segmentation information for the token */
    @Required
    @Size(max = 1000)
    public String segmentation;

    /** Reading (pronunciation) of the token in katakana */
    @Required
    @Size(max = 1000)
    public String reading;

    /** Part of speech tag for the token */
    @Required
    @Size(max = 1000)
    public String pos;

    /**

    // --- as(Class, DLSequence, int) ---

    @Test
    void testAs_DLSequence_RecursiveBug() {
        // This test exposes a recursive bug in the current implementation
        // The method calls itself, leading to a StackOverflowError.
        ASN1EncodableVector vector = new ASN1EncodableVector();
        vector.add(new ASN1Integer(10));
        DLSequence sequence = new DLSequence(vector);

    public Integer crudMode;

    /** The word that should trigger document elevation in search results */
    @Required
    public String suggestWord;

    /** The reading/pronunciation of the suggest word for language analysis */
    public String reading;

    /** The target label for filtering documents to be elevated */
    public String targetLabel;