@bntk/ner/index.d.ts

Build applications with Bengali natural language processing tools.

/**
 * Represents a named entity found in text with its position and classification details.
 * @interface
 * @property {string} text - The actual text of the entity
 * @property {EntityType} type - The classification type of the entity
 * @property {number} start - Starting position of the entity in the text
 * @property {number} end - Ending position of the entity in the text
 * @property {number} confidence - Confidence score of the classification (0-1)
 */
export interface Entity {
    text: string;
    type: EntityType;
    start: number;
    end: number;
    confidence: number;
}
/**
 * Enumeration of supported named entity types.
 * @enum {string}
 */
export declare enum EntityType {
    PERSON = "PERSON",
    ORGANIZATION = "ORGANIZATION",
    LOCATION = "LOCATION",
    DATE = "DATE",
    MONEY = "MONEY",
    PERCENT = "PERCENT",
    TIME = "TIME",
    UNKNOWN = "UNKNOWN"
}
/**
 * Extracts named entities from input text.
 * @param {string} text - The input text to analyze
 * @returns {Entity[]} Array of detected entities with their positions and classifications
 * @example
 * const entities = extractEntities("John Doe works at Apple Inc.");
 * // Returns: [{text: "John Doe", type: "PERSON", start: 0, end: 8, confidence: 0.95}]
 */
export declare function extractEntities(text: string): Entity[];
/**
 * Classifies a single text segment into an entity type.
 * @param {string} text - The text to classify
 * @returns {EntityType} The predicted entity type
 * @example
 * const type = classifyEntity("John Doe");
 * // Returns: EntityType.PERSON
 */
export declare function classifyEntity(text: string): EntityType;
/**
 * Calculates confidence score for entity classification.
 * @param {string} text - The text to analyze
 * @param {EntityType} entityType - The entity type to check
 * @returns {number} Confidence score between 0 and 1
 * @example
 * const confidence = getEntityConfidence("John Doe", EntityType.PERSON);
 * // Returns: 0.85
 */
export declare function getEntityConfidence(text: string, entityType: EntityType): number;
/**
 * Processes multiple texts for entity extraction in batch.
 * @param {string[]} texts - Array of texts to process
 * @returns {Entity[][]} Array of entity arrays for each input text
 * @example
 * const results = batchExtractEntities(["John Doe", "New York"]);
 * // Returns: [[{text: "John Doe", ...}], [{text: "New York", ...}]]
 */
export declare function batchExtractEntities(texts: string[]): Entity[][];
/**
 * Retrieves all supported entity types.
 * @returns {EntityType[]} Array of all supported entity types
 * @example
 * const types = getSupportedEntityTypes();
 * // Returns: [EntityType.PERSON, EntityType.ORGANIZATION, ...]
 */
export declare function getSupportedEntityTypes(): EntityType[];