Pyserini

Pyserini is an open-source software toolkit for information retrieval and retrieval-based natural language processing. It focuses on passage ranking, question answering, and document ranking tasks. The toolkit supports a range of data sets, including a subset of the TREC DL2008 corpora.

Pyserini uses the ANSER library, which is a more extensive toolkit for retrieval-based natural language processing. It is written in Python and utilizes the Pyserini library to run experiments and leverage its implementation of efficient indexing and retrieval algorithms.

One of the primary strengths of Pyserini is its reliance on the popular TF-IDF algorithm for document representations. It also incorporates techniques for efficient ranking of large collections of text and supports distributed computing for large document sets.

The toolkit supports several different retrieval models, including baselines and modern methods like support vector machines, gradient boosting, and learned metrics-based models. While it focuses on a relatively narrow set of retrieval tasks, Pyserini is highly extensible and can be employed as a base for additional work in areas beyond its scope.

Pyserini draws from and extends the work of other notable retrieval software to provide a general-purpose framework for working on a specific set of tasks. It uses its foundation and the success of related toolkits as a starting point to fill the gap in a more limited set of retrieval-based NLP tasks.