  We describe SLING, a framework for parsing natural language into semantic
frames. SLING supports general transition-based, neural-network parsing with
bidirectional LSTM input encoding and a Transition Based Recurrent Unit (TBRU)
for output decoding. The parsing model is trained end-to-end using only the
text tokens as input. The transition system has been designed to output frame
graphs directly without any intervening symbolic representation. The SLING
framework includes an efficient and scalable frame store implementation as well
as a neural network JIT compiler for fast inference during parsing. SLING is
implemented in C++ and it is available for download on GitHub.
