ab-ai/PII-Dataset-English-43K

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Named Entity Recognition (NER) Dataset

This repository contains a dataset for Named Entity Recognition (NER) tasks, focusing on identifying various types of entities in textual data.

Dataset Summary

The dataset is designed to help train and evaluate models for recognizing and classifying entities in text. The entities are labeled with different tags such as names, dates, email addresses, phone numbers, URLs, and other identifiers.

Supported Tasks and Leaderboards

• Named Entity Recognition (NER): This dataset can be used to train and evaluate models for recognizing and classifying entities in text.
• Information Extraction: Useful for extracting structured information from unstructured text.

Languages

The dataset is in English.

Dataset Structure

Data Instances

Each instance in the dataset consists of:

• text: The original sentence.
• words: The tokenized words from the sentence.
• ner_labels: The NER labels corresponding to each token.

Here is a sample from the dataset:

{
  "text": "Student Willow Mueller has opted for the school meal plan. The fees have been debited from 61148293.",
  "words": ["Student", "Willow", "Mueller", "has", "opted", "for", "the", "school", "meal", "plan.", "The", "fees", "have", "been", "debited", "from", "61148293."],
  "ner_labels": ["O", "B-FIRSTNAME", "B-LASTNAME", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-ACCOUNTNUMBER"]
}