Datasets:
dataset_info:
features:
- name: ID
sequence: int64
- name: Word
sequence: string
- name: Lemma
sequence: string
- name: POS
sequence: string
- name: Definition
sequence: string
- name: Lemma_sentence
dtype: string
- name: sentence
dtype: string
- name: Lemma_tfidf
sequence: string
- name: Lemma_tfidf_value
sequence: float64
splits:
- name: train
num_bytes: 24209901
num_examples: 20138
download_size: 8568417
dataset_size: 24209901
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: mit
task_categories:
- text-classification
language:
- en
size_categories:
- 1K<n<10K
Dataset Card for "SemCor – sense-tagged English corpus"
Description
This dataset is derived from the wsd_semcor dataset, originally hosted on Hugging Face. It has been preprocessed for tasks related to Word Sense Disambiguation (WSD) and WordNet integration.
Preprocessing
The original text data underwent the following preprocessing steps:
- Text splitting into individual words (lemmas).
- TF-IDF (Term Frequency-Inverse Document Frequency) analysis to understand the importance of words within the documents.
Structure
The dataset contains:
- Lemmas: Words obtained from splitting the text data.
- TF-IDF values: Quantitative measures of word importance within the documents.
Note
The number of elements in Lemma and Lemma_tfidf might not match. This is because Lemma is based on original dataset and might contain compound words, which might not be recognized by TF-IDF algorithm.
Intended Use
This dataset is intended for use in WSD and WordNet integration tasks. It provides foundational data for natural language processing (NLP) research and applications, specifically focusing on understanding word meanings and contextual usage.
Citation
Data sourced from wsd_semcor dataset on Hugging Face.