code: def movie_reviews_data_negative():
      """Dataset of single sentence samples labeled negative."""
      download_nltk_resources()
      random.seed(42)
      neg_sentences = [
          " ".join(x) for x in movie_reviews.sents(categories="neg")
      ]
      neg_data = TextData(
          random.choices(neg_sentences, k=1000), name="Negative"
      )
      return neg_data
  
imports: import random
  import typing
  import numpy
  import pytest
  from datasets import load_dataset
  from nltk import download
  from nltk.corpus import movie_reviews
  from deepchecks.nlp.datasets.classification import just_dance_comment_analysis, tweet_emotion
  from deepchecks.nlp.text_data import TextData
label_desc: Use image node_id 15 for calling a global function with example usage: movie_reviews_data_negative() and returns: neg_data