1,865 research outputs found
Synchronous Context-Free Grammars and Optimal Linear Parsing Strategies
Synchronous Context-Free Grammars (SCFGs), also known as syntax-directed
translation schemata, are unlike context-free grammars in that they do not have
a binary normal form. In general, parsing with SCFGs takes space and time
polynomial in the length of the input strings, but with the degree of the
polynomial depending on the permutations of the SCFG rules. We consider linear
parsing strategies, which add one nonterminal at a time. We show that for a
given input permutation, the problems of finding the linear parsing strategy
with the minimum space and time complexity are both NP-hard
Data-Oriented Parsing with Discontinuous Constituents and Function Tags
Statistical parsers are e ective but are typically limited to producing projective dependencies or constituents. On the other hand, linguisti- cally rich parsers recognize non-local relations and analyze both form and function phenomena but rely on extensive manual grammar development. We combine advantages of the two by building a statistical parser that produces richer analyses. We investigate new techniques to implement treebank-based parsers that allow for discontinuous constituents. We present two systems. One system is based on a string-rewriting Linear Context-Free Rewriting System (LCFRS), while using a Probabilistic Discontinuous Tree Substitution Grammar (PDTSG) to improve disambiguation performance. Another system encodes the discontinuities in the labels of phrase structure trees, allowing for efficient context-free grammar parsing. The two systems demonstrate that tree fragments as used in tree-substitution grammar improve disambiguation performance while capturing non-local relations on an as-needed basis. Additionally, we present results of models that produce function tags, resulting in a more linguistically adequate model of the data. We report substantial accuracy improvements in discontinuous parsing for German, English, and Dutch, including results on spoken Dutch
Data-Oriented Parsing with discontinuous constituents and function tags
Statistical parsers are e ective but are typically limited to producing projective dependencies or constituents. On the other hand, linguisti- cally rich parsers recognize non-local relations and analyze both form and function phenomena but rely on extensive manual grammar development. We combine advantages of the two by building a statistical parser that produces richer analyses.
We investigate new techniques to implement treebank-based parsers that allow for discontinuous constituents. We present two systems. One system is based on a string-rewriting Linear Context-Free Rewriting System (LCFRS), while using a Probabilistic Discontinuous Tree Substitution Grammar (PDTSG) to improve disambiguation performance. Another system encodes the discontinuities in the labels of phrase structure trees, allowing for efficient context-free grammar parsing.
The two systems demonstrate that tree fragments as used in tree-substitution grammar improve disambiguation performance while capturing non-local relations on an as-needed basis. Additionally, we present results of models that produce function tags, resulting in a more linguistically adequate model of the data. We report substantial accuracy improvements in discontinuous parsing for German, English, and Dutch, including results on spoken Dutch
Neural Combinatory Constituency Parsing
東京都立大学Tokyo Metropolitan University博士(情報科学)doctoral thesi
Generalizing input-driven languages: theoretical and practical benefits
Regular languages (RL) are the simplest family in Chomsky's hierarchy. Thanks
to their simplicity they enjoy various nice algebraic and logic properties that
have been successfully exploited in many application fields. Practically all of
their related problems are decidable, so that they support automatic
verification algorithms. Also, they can be recognized in real-time.
Context-free languages (CFL) are another major family well-suited to
formalize programming, natural, and many other classes of languages; their
increased generative power w.r.t. RL, however, causes the loss of several
closure properties and of the decidability of important problems; furthermore
they need complex parsing algorithms. Thus, various subclasses thereof have
been defined with different goals, spanning from efficient, deterministic
parsing to closure properties, logic characterization and automatic
verification techniques.
Among CFL subclasses, so-called structured ones, i.e., those where the
typical tree-structure is visible in the sentences, exhibit many of the
algebraic and logic properties of RL, whereas deterministic CFL have been
thoroughly exploited in compiler construction and other application fields.
After surveying and comparing the main properties of those various language
families, we go back to operator precedence languages (OPL), an old family
through which R. Floyd pioneered deterministic parsing, and we show that they
offer unexpected properties in two fields so far investigated in totally
independent ways: they enable parsing parallelization in a more effective way
than traditional sequential parsers, and exhibit the same algebraic and logic
properties so far obtained only for less expressive language families
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