Discepency in the qrels
Hello,
In the qrels split of the dataset, there are corpus ids that start with 6:, whereas all the corpus ids in the corpus split all the corpus ids start with 5:. How to correct this mapping?
Hi, the qrel-to-corpus mapping is inherited from the original M-BEIR dataset: https://huggingface.co/datasets/TIGER-Lab/M-BEIR.
After review, I’ve confirmed that the issue originates from the original data.
I recommend cleaning the qrels by removing redundant positive entries before calculating the metrics.
Hello, thanks for responding. I am not sure what is inferred by 'I recommend cleaning the qrels by removing redundant positive entries before calculating the metrics.' Do we get rid of all the entries with '6:' in the corpus id from the qrels. Could you please elaborate a bit more on this?
Sure, you can use the following script to clean the qrels.
from datasets import load_dataset
import pandas as pd
from tqdm import tqdm
import logging
def clean_qrels(corpus_dataset, qrels_dataset, output_path=None):
"""
Clean qrels by removing entries where the document ID doesn't exist in the corpus.
Args:
corpus_dataset: HuggingFace dataset containing the corpus
qrels_dataset: HuggingFace dataset containing the qrels
output_path: Optional path to save the cleaned qrels as CSV
Returns:
cleaned_qrels: Pandas DataFrame containing the cleaned qrels
"""
# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# Convert corpus to set of IDs for faster lookup
logger.info("Creating set of corpus document IDs...")
corpus_ids = set(corpus_dataset['id'])
# Convert qrels to pandas for easier processing
logger.info("Converting qrels to DataFrame...")
qrels_df = pd.DataFrame({
'query-id': qrels_dataset['query-id'],
'Q0': qrels_dataset['Q0'],
'corpus-id': qrels_dataset['corpus-id'],
'score': qrels_dataset['score']
})
# Get initial statistics
initial_count = len(qrels_df)
# Filter qrels to only include existing documents
logger.info("Filtering qrels...")
cleaned_qrels = qrels_df[qrels_df['corpus-id'].isin(corpus_ids)]
# Get final statistics
final_count = len(cleaned_qrels)
removed_count = initial_count - final_count
# Log statistics
logger.info(f"Initial qrels count: {initial_count}")
logger.info(f"Final qrels count: {final_count}")
logger.info(f"Removed {removed_count} entries ({(removed_count/initial_count)*100:.2f}%)")
# Save to file if output path is provided
if output_path:
logger.info(f"Saving cleaned qrels to {output_path}")
cleaned_qrels.to_csv(output_path, index=False)
return cleaned_qrels
if __name__ == "__main__":
# Load datasets
corpus = load_dataset('MRBench/mbeir_oven_task6', 'corpus', split='corpus')
qrels = load_dataset('MRBench/mbeir_oven_task6', 'qrels', split='test')
# Clean qrels
cleaned_qrels = clean_qrels(
corpus_dataset=corpus,
qrels_dataset=qrels,
output_path="cleaned_qrels.csv"
)