metadata

language:
  - it
license: cc-by-nc-sa-4.0
dataset_info:
  features:
    - name: id
      dtype: string
    - name: prompt
      dtype: string
    - name: target
      dtype: string
    - name: class
      dtype:
        class_label:
          names:
            '0': not_follow
            '1': follow
    - name: source
      dtype: string
  splits:
    - name: train
      num_bytes: 9263673
      num_examples: 16000
    - name: test
      num_bytes: 932051
      num_examples: 1600
  download_size: 6727616
  dataset_size: 10195724
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*

DisCoTEX - Last Sentence Classification

Disclaimer: This dataset is not the official DisCoTEX repository from EVALITA. For the official repository and more information, please visit the EVALITA DiscoTEX page or the DiscoTEX repository.

Overview

The DisCoTEX dataset is part of the DisCoTEX shared task at EVALITA 2023, aimed at assessing discourse coherence in Italian texts. This dataset focuses on Italian real-world texts and provides resources to model coherence in natural language. The dataset comprises texts from two distinct sources: Italian Wikipedia and the Multilingual TEDx corpus (mTEDx), representing different language varieties and genres.

Dataset Description

Structure:

The dataset consists of text passages containing four consecutive sentences, used as the unit of analysis. For Wikipedia, paragraphs were used to select four-sentence segments. For TEDx, transcripts were automatically split into four-sentence passages. The dataset is balanced between follow and not_follow classes; in the not_follow class, 20% of the targets are sentences from a different document, and 80% are the 10th sentence after the prompt in the same document.

Format:

The dataset is composed of:

id: Identifier for the entry.
prompt: A snippet of text (3 sentences).
target: The sentence to assess for coherence with the prompt.
class: follow if target is the last sentence of the passage not_follow otherwise
source: Source of the sample, either mTEDx or wikipedia