/// <summary>
/// Name entity recognition identifies specific entities in sentences. With the current models, you can detect persons, dates, locations, money, percentages and time
/// </summary>
/// <param name="txt">Texto de input</param>
/// <param name="tags">string[] com a designação das tags possíveis de etiquetar: "date", "location", "money", "organization", "percentage", "person", "time"</param>
/// <returns>retorna o texto etiquetado</returns>
public static string NER(this string txt, string[] tags)
{
//Tive que fazer download da diretoria
//Não esquecer de adicionar using OpenNLP.Tools.NameFind;
var modelPath3 = Path + @"NameFind\";
var nameFinder = new EnglishNameFinder(modelPath3);
string ner = nameFinder.GetNames(tags, txt);
return(ner);
}
private string FindNames(Parse sentenceParse)
{
if (_nameFinder == null)
{
_nameFinder = new EnglishNameFinder(_modelPath + "namefind\\");
}
var models = new[] { "date", "location", "money", "organization", "percentage", "person", "time" };
return(_nameFinder.GetNames(models, sentenceParse));
}
private string MyNer(string sentence)
{
var modelPath = Path.GetDirectoryName(Process.GetCurrentProcess().MainModule.FileName) + @"\Models\NameFind\";
var nameFinder = new EnglishNameFinder(modelPath);
// specify which types of entities you want to detect
string[] models = new string[7];//MySentenceDetector("date. location. money. organization. percentage. person. time");
models[0] = "date";
models[1] = "location";
models[2] = "money";
models[3] = "organization";
models[4] = "percentage";
models[5] = "person";
models[6] = "time";
var ner = nameFinder.GetNames(models, sentence);
return(ner);
}
