Minimalist Parsing
NWO-VENI grant project on neural parsing into Minimalist Grammars, and their use in semantic parsing.
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Semantic parsing using the Apply-Modify Algebra for graphs
Joint work with Jonas Groschwitz, Matthias Lindemann, and Alexander Koller
- CONLL shared task: Donatelli, L., Fowlie, M., Groschwitz, J., Koller, A., Lindemann, M., Mina, M.M., & Weißenhorn, P. (2019). Saarland at MRP 2019: Compositional parsing across all graphbanks. CoNLL Shared Task.
- ACL 2018: AMR dependency parsing with a Typed Semantic Algebra: treating AMR composition with the AM-algebra as a form of dependency parsing
- A constrained graph algebra for semantic parsing with AMRs (IWCS 2017): a typed algebra (the Apply-Modify (AM) Algebra) for compositionally building and decomposing AMR graphs
Learnability of optionality and repetition
- As adjuncts are classically
optionally and often repeatable, it is useful to see how
formal learning algorithms approach optionality and
repetition. Some learners treat optionality and repetition as a
unified phenomenon. Click here for more
details
Mathematical models of syntax
- Parsing Minimalist Languages with Interpreted Regular Tree Grammars
- TAG+ 2017 paper
- Joint work with Alexander Koller
- Using IRTG parsing, we show that MG parsing complexity is O(n2k+3) (for k = the number of licensing features), rather than O(n4k+4) as previously thought
- Minimalist Grammars with Adjunction
- Multidominant Minimalist Grammars
- A minimalist grammar that generates multidominant graphs,
a structure that retains information about the derivation,
allowing moved constituent to easily be interpreted correctly in
each of their positions. Click here for more details
Formal Language Theory, especially subregular tree languages