  Information retrieval based knowledge base question answering (KBQA) first
retrieves a subgraph to reduce search space, then reasons on the subgraph to
select answer entities. Existing approaches have three issues that impede the
retrieval of such subgraphs. Firstly, there is no off-the-shelf toolkit for
semantic-relevant subgraph retrieval. Secondly, existing methods are
knowledge-graph-dependent, resulting in outdated knowledge graphs used even in
recent studies. Thirdly, previous solutions fail to incorporate the best
available techniques for entity linking or path expansion. In this paper, we
present SRTK, a user-friendly toolkit for semantic-relevant subgraph retrieval
from large-scale knowledge graphs. SRTK is the first toolkit that streamlines
the entire lifecycle of subgraph retrieval across multiple knowledge graphs.
Additionally, it comes with state-of-the-art subgraph retrieval algorithms,
guaranteeing an up-to-date solution set out of the box.
