Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering
Table 3: Zero-shot (zs) IR results on Wikihop.
['Model', 'acc@2', 'acc@5']
We assign the first entity mention occurring in a paragraph as the textual description of that entity. For instance, if the first entity mention in the paragraph is ‘Mumbai’, we assign that paragraph as the textual description for the entity ‘Mumbai’. This assumption is often true for the introductory paragraphs of a Wikipedia article. Next, we perform entity linking of mentions by just simple string matching (i.e. linking strings such as ‘mumbai’ to the previous paragraph). After constructing a small subgraph from the candidate paragraphs, we apply our model trained on HotpotQA. The baseline models we compare to are a BM25 retriever and a Bert-re-ranker model of (nogueira2019passage) that ranks all the candidate supporting paragraphs for the question.