houveríamos
houveriam
sou
somos
são
era
éramos
eram
fui
foi
fomos
foram
fora
fôramos
seja
sejamos
sejam
fosse
fôssemos
fossem
for
formos
forem
serei
será
seremos
serão
seria
seríamos
seriam
tenho
tem
temos
tém
tinha
tínhamos
tinham
tive
teve
tivemos
tiveram
tivera
tivéramos
tenha

"houveremos", "houverão", "houveria", "houveríamos", "houveriam", "sou", "somos", "são", "era", "éramos", "eram", "fui", "foi", "fomos", "foram", "fora", "fôramos", "seja", "sejamos", "sejam", "fosse", "fôssemos", "fossem", "for", "formos", "forem", "serei", "será", "seremos", "serão", "seria", "seríamos", "seriam", "tenho", "tem", "temos", "tém", "tinha", "tínhamos", "tinham", "tive", "teve", "tivemos", "tiveram", "tivera", "tivéramos", "tenha", "tenhamos", "tenham", "tivesse", "tivéssemos", "tivessem",...

"houveremos", "houverão", "houveria", "houveríamos", "houveriam", "sou", "somos", "são", "era", "éramos", "eram", "fui", "foi", "fomos", "foram", "fora", "fôramos", "seja", "sejamos", "sejam", "fosse", "fôssemos", "fossem", "for", "formos", "forem", "serei", "será", "seremos", "serão", "seria", "seríamos", "seriam", "tenho", "tem", "temos", "tém", "tinha", "tínhamos", "tinham", "tive", "teve", "tivemos", "tiveram", "tivera", "tivéramos", "tenha", "tenhamos", "tenham", "tivesse", "tivéssemos", "tivessem",...

fueseis
fuesen
siendo
sido
tengo
tienes
tiene
tenemos
tenéis
tienen
tenga
tengas
tengamos
tengáis
tengan
tendré
tendrás
tendrá
tendremos
tendréis
tendrán
tendría
tendrías
tendríamos
tendríais
tendrían
tenía
tenías
teníamos
teníais
tenían
tuve
tuviste
tuvo
tuvimos
tuvisteis
tuvieron
tuviera
tuvieras

        /**
         * Constructs a Field from OpenSearch Terms aggregation.
         * Decodes the field name and processes all term buckets to extract
         * field values and their document counts.
         *
         * @param termFacet the OpenSearch Terms aggregation containing field facet data
         */
        public Field(final Terms termFacet) {

import org.opensearch.search.aggregations.bucket.histogram.DateHistogramInterval;
import org.opensearch.search.aggregations.bucket.histogram.Histogram;
import org.opensearch.search.aggregations.bucket.terms.Terms;
import org.opensearch.search.aggregations.metrics.Avg;
import org.opensearch.search.aggregations.metrics.Cardinality;

import jakarta.annotation.Resource;

/**

    /** CRUD operation mode (CREATE, EDIT, etc.) */
    @ValidateTypeFailure
    public Integer crudMode;

    /** Input terms (comma-separated) that will be mapped to the output term */
    @Required
    @Size(max = 1000)
    public String inputs;

    /** Output term that input terms will be mapped to */
    @Size(min = 1, max = 1000)
    public String output;

    /**

    /** The CRUD operation mode for form processing */
    @ValidateTypeFailure
    public Integer crudMode;

    /** The input terms that should be considered synonymous */
    @Required
    @Size(max = 1000)
    public String inputs;

    /** The output synonyms that should be matched for the input terms */
    @Required
    @Size(max = 1000)
    public String outputs;

    /**

        final Term[] terms = phraseQuery.getTerms();
        if (terms.length == 0) {
            throw new InvalidQueryException(messages -> messages.addErrorsInvalidQueryUnknown(UserMessages.GLOBAL_PROPERTY_KEY),
                    "Unknown phrase query: " + phraseQuery);
        }
        final FessConfig fessConfig = ComponentUtil.getFessConfig();
        final String field = terms[0].field();

    protected String defaultField = Constants.DEFAULT_FIELD;

    /** The analyzer used to analyze query terms */
    protected Analyzer analyzer = new WhitespaceAnalyzer();

    /** Whether to allow leading wildcards in query terms */
    protected boolean allowLeadingWildcard = true;

    /** The default operator to use between query terms */
    protected Operator defaultOperator = Operator.AND;

    /** List of filters to apply to queries */