Dependency and constituent trees are widely used by many artificial intelligence
applications for representing the syntactic structure of human languages. Typically, these …

We introduce a novel chart-based algorithm for span-based parsing of discontinuous
constituency trees of block degree two, including ill-nested structures. In particular, we show …

Text classification is one of the most important and typical tasks in Natural Language
Processing (NLP) which can be applied for many applications. Recently, deep learning …

This paper develops a novel psycholinguistic parser and tests it against experimental and
corpus reading data. The parser builds on the recent research into memory structures, which …

Lexicalized parsing models are based on the assumptions that (i) constituents are organized
around a lexical head and (ii) bilexical statistics are crucial to solve ambiguities. In this …

One of the most complex syntactic representations used in computational linguistics and
NLP are discontinuous constituent trees, crucial for representing all grammatical …

This paper reduces discontinuous parsing to sequence labeling. It first shows that existing
reductions for constituent parsing as labeling do not support discontinuities. Second, it fills …

We introduce a novel transition system for discontinuous constituency parsing. Instead of
storing subtrees in a stack--ie a data structure with linear-time sequential access--the …

We define a mapping from transition-based parsing algorithms that read sentences from left
to right to sequence labeling encodings of syntactic trees. This not only establishes a …

As opposed to word sense induction, word sense disambiguation (WSD), whether
supervised or semi-supervised, has the advantage of using interpretable senses, but …