Parsing Performance

This paper describes an empirical study on the op- timal granularity of the phrase structure rules and the optimal strategy for interleaving CFG parsing with unification in order to implement …...

Alter presenting a novel O(n a) parsing al- gorithm for dependency grammar, we de- velop three contrasting ways to stochasticize it. We propose (a) a lexical atfinity mode] where words …...

We present an empirical study of the applica- bility of Probabilistic Lexicalized Tree Inser- tion Grammars (PLTIG), a lexicalized counter- part to Probabilistic Context-Free Grammars (PCFG), to problems in stochastic …...

Treebanks, such as the Penn Treebank (PTB), offer a simple approach to obtaining a broad coverage grammar: one can simply read the grammar off the parse trees in the treebank. …...

Each year the Conference on Com- putational Natural Language Learning (CoNLL)1 features a shared task, in which participants train and test their systems on exactly the same data sets, in …...

AbstractWe evaluate statistical parsing of French using two probabilistic models derived from the Tree Adjoining Grammar framework: a Stochastic Tree Insertion Grammars model (STIG) and a specific instance of this …...

There is often more than one way to represent syntactic structures, even within a given formalism. Selecting one representation over another may affect parsing performance. Therefore, selecting between alternative syntactic …...

For languages such as English, several constituent-to-dependency conversion schemes are pro- posed to construct corpora for dependency parsing. It is hard to determine which scheme is better because they reflect …...

Completely data-driven grammar training is prone to over-fitting. Human-defined word class knowledge is useful to address this issue. However, the manual word class taxonomy may be unreliable and irrational for …...

We present a transition-based parser that jointly produces syntactic and semantic dependencies. It learns a representation of the entire algorithm state, using stack long short-term memories. Our greedy in- ference …...

AbstractThe growing work in multi-lingual parsing faces the challenge of fair comparative evaluation and performance analysis across languages and their treebanks. The difficulty lies in teasing apart the properties of …...

There has been almost no work on phrase structure annotation and parsing specially designed for learner English despite the fact that they are useful for representing the structural characteristics of …...

AbstractWe present an analysis on the effect UPOS accuracy has on parsing performance. Results suggest that leveraging UPOS tags as fea-tures for neural parsers requires a prohibitively high tagging accuracy …...

AbstractAbstract Meaning Representation (AMR) parsing aims at converting sentences into AMR representations. These are graphs and not trees because AMR supports reentrancies (nodes with more than one parent). Following previous …...

Using multiple treebanks to improve parsing performance has shown positive results. How- ever, to what extent similar, yet competing an- notation decisions play in parser behavior is unclear. We investigate …...

AbstractCurrent multilingual semantic parsing (MSP) datasets are almost all collected by translating the utterances in the existing datasets from the resource-rich language to the target language. However, manual translation is …...