import sys import config_data sys.path.append(config_data.jarvis_folder_location) from JarvisN.database.datahelper import DataDbHelper td = [] dbh = DataDbHelper() result = dbh.getResult( "SELECT sentence, label2 FROM trainingdata WHERE label1='dictionary'") dbh.closeConnection() for row in result: td.append((row[0], row[1])) print(td)
from nltk.tokenize import word_tokenize from nltk.classify.scikitlearn import SklearnClassifier from sklearn.naive_bayes import MultinomialNB, BernoulliNB from sklearn.linear_model import LogisticRegression, SGDClassifier from sklearn.svm import SVC, LinearSVC, NuSVC import sys import os sys.path.append(r"C:\Users\Dhaval\Documents\GitHub" ) # Your JarvisN folder Location... Replace it from JarvisN.database.datahelper import DataDbHelper # Rename folder to JarvisN not JarvisN-Master #td = [] dbh = DataDbHelper() #result = dbh.getResult("SELECT sentence, label1 FROM trainingdata") # execute ur query here result = dbh.getResult( "SELECT sentence, entitys, entitye, entity FROM trainingdata WHERE label1='music'" ) # execute ur query here dbh.closeConnection() file = open('nerData.tsv', 'w') for row in result: sentence = row[0].split(" ") start = row[1] end = row[2] if row[3] == 'none': continue print(start, end) i = 0 for word in sentence: if i >= start and i < end: file.write(word + "\t" + row[3]) #if (end - start) == 1: