Semantic Parsing

  • TreeDRS parser, described in Liu et al. (ACL, 2019).
  • Discourse Representation Theory  (DRT) parser described in Liu et al. (ACL, 2018).
  • MATE, MultiSeed Aspect Extractor Model (EMNLP, 2018)
  • SCANNER, neural semantic parser described in Cheng et al (ACL, 2017).
  • UDepLambda, framework to convert universal dependencies to logical form (EMNLP, 2017).
  • DepLambda, code for transforming dependency structures to logical form (TACL, 2016).
  • Lang2Logic, semantic parsers descibed in Dong and Lapata (ACL, 2016).
  • GraphParser, (ungrounded) semantic parser described in Reddy et al. (TACL, 2014).


Semantic Role Labeling


Representation Learning

  • Weakly supervised domain detection in Xu and Lapata (TACL, 2019).
  • MILNET, multiple instance learning networks for fine-grained sentiment analysis, described in Angelidis and Lapata (TACL, 2018).
  • Generative parser, described in Cheng et al (ACL, 2017).
  • DenSe parser, code for neural dependency parser described in Zhang et al. (EACL, 2017).
  • Long short term memory networks, code for LSTMN described in Cheng et al. (EMNLP, 2016).
  • TreeLSTM, code for models described in Zhang et al. (NAACL, 2016).
  • Dependency Vectors, software for semantic spaces described in Pado and Lapata (CL, 2007).