license: apache-2.0
task_categories:
- question-answering
language:
- ur
size_categories:
- ~50GB
Dataset Card for Dataset Name
This dataset is the translation of the MS-marco dataset, marking it the first large-scale urdu IR dataset.
Dataset Details
The MS MARCO dataset is formed by a collection of 8.8M passages, approximately 530k queries, and at least one relevant passage per query, which were selected by humans. The development set of MS MARCO comprises more than 100k queries. However, a smaller set of 6,980 queries is used for evaluation in most published works.
The triples files (triples.train.small.urdu.tsv , named as triple files part aa to ae) is around 47 GB and is split into 5 parts. Download them and combine them before you start working.
This dataset is created using the IndicTrans2 translation model.
Dataset Description
The MS MARCO dataset's Urdu version comprises several files, each serving a distinct purpose in information retrieval tasks. Below is an overview of each file along with its structure:
triples.train.small.urdu.tsv:
Purpose: Contains training data formatted as triples for ranking models. Structure: Each line includes a query, a relevant passage (positive example), and a non-relevant passage (negative example), separated by tabs. Sample Entry:
< query > \t < positive_passage > \t < negative_passage >
urdu_collection.tsv:
Purpose: Comprises the entire collection of Urdu documents in the dataset. Structure: Each line contains a document ID and the corresponding document text, separated by a tab. Sample Entry:
< doc_id > \t < document_text >
urdu_collection_small.tsv:
Purpose: A subset of the full collection, containing 2,000 documents for preliminary experiments. Structure: Similar to urdu_collection.tsv, with each line containing a document ID and the corresponding document text. Sample Entry:
< doc_id > \t < document_text >
urdu_queries.dev.small.tsv:
Purpose: Includes a small set of development (validation) queries in Urdu. Structure: Each line contains a query ID and the corresponding query text, separated by a tab. Sample Entry:
< query_id > \t < query_text >
urdu_queries.dev.tsv:
Purpose: Provides a more extensive set of development queries for validating model performance. Structure: Each line contains a query ID and the corresponding query text, separated by a tab. Sample Entry:
< query_id > \t < query_text >
urdu_queries.train.tsv:
Purpose: Contains the training queries in Urdu, each paired with relevant documents. Structure: Each line includes a query ID and the corresponding query text, separated by a tab. Sample Entry:
< query_id > \t < query_text >
These files collectively support the development and evaluation of retrieval models in Urdu, enabling research in multilingual information retrieval.
Bias, Risks, and Limitations
Because this is a machine translated dataset so the limitations of the machine translation model (IndicTrans2) apply here.
Dataset Card Authors
Umer Butt