midas/krapivin

Dataset Summary

A dataset for benchmarking keyphrase extraction and generation techniques from long document english scientific papers. For more details about the dataset please refer the original paper - https://www.semanticscholar.org/paper/Large-Dataset-for-Keyphrases-Extraction-Krapivin-Autaeu/2c56421ff3c2a69894d28b09a656b7157df8eb83 Original source of the data -

Dataset Structure

Data Fields

• id: unique identifier of the document.
• document: Whitespace separated list of words in the document.
• doc_bio_tags: BIO tags for each word in the document. B stands for the beginning of a keyphrase and I stands for inside the keyphrase. O stands for outside the keyphrase and represents the word that isn't a part of the keyphrase at all.
• extractive_keyphrases: List of all the present keyphrases.
• abstractive_keyphrase: List of all the absent keyphrases.

Data Splits

Split	#datapoints
Test	2305

Usage

Full Dataset

from datasets import load_dataset

# get entire dataset
dataset = load_dataset("midas/krapivin", "raw")

# sample from the test split
print("Sample from test dataset split")
test_sample = dataset["test"][0]
print("Fields in the sample: ", [key for key in test_sample.keys()])
print("Tokenized Document: ", test_sample["document"])
print("Document BIO Tags: ", test_sample["doc_bio_tags"])
print("Extractive/present Keyphrases: ", test_sample["extractive_keyphrases"])
print("Abstractive/absent Keyphrases: ", test_sample["abstractive_keyphrases"])
print("\n-----------\n")

Output

Keyphrase Extraction

from datasets import load_dataset

# get the dataset only for keyphrase extraction
dataset = load_dataset("midas/krapivin", "extraction")

print("Samples for Keyphrase Extraction")

# sample from the test split
print("Sample from test data split")
test_sample = dataset["test"][0]
print("Fields in the sample: ", [key for key in test_sample.keys()])
print("Tokenized Document: ", test_sample["document"])
print("Document BIO Tags: ", test_sample["doc_bio_tags"])
print("\n-----------\n")

Keyphrase Generation

# get the dataset only for keyphrase generation
dataset = load_dataset("midas/krapivin", "generation")

print("Samples for Keyphrase Generation")

# sample from the test split
print("Sample from test data split")
test_sample = dataset["test"][0]
print("Fields in the sample: ", [key for key in test_sample.keys()])
print("Tokenized Document: ", test_sample["document"])
print("Extractive/present Keyphrases: ", test_sample["extractive_keyphrases"])
print("Abstractive/absent Keyphrases: ", test_sample["abstractive_keyphrases"])
print("\n-----------\n")

Citation Information

@inproceedings{Krapivin2009LargeDF,
  title={Large Dataset for Keyphrases Extraction},
  author={Mikalai Krapivin and Aliaksandr Autaeu and Maurizio Marchese},
  year={2009}
}

Contributions

Thanks to @debanjanbhucs, @dibyaaaaax and @ad6398 for adding this dataset