diff --git a/README.rst b/README.rst index af3392f50..360aeac97 100644 --- a/README.rst +++ b/README.rst @@ -21,8 +21,6 @@ Core Features Components ========== -There are three major components for the question answering pipeline: - 1. **Retriever**: Fast, simple model that identify candidate passages from a large collection of documents. Algorithms include TF-IDF, which is similar to what's used in popular search systems like Elasticsearch. The Retriever helps to narrow down the scope for Reader to smaller units of text where a given question could be answered. 2. **Reader**: Powerful neural model that read through texts in detail to find an answer. Use diverse models like BERT, Roberta or XLNet trained via the `FARM `_ Framework on SQuAD like tasks. The Reader takes multiple passages of text as input and returns top-n answers with corresponding confidence scores.