concepts.language.neural_ccg.grammar#

The grammar components for neural CCGs, including syntax types, semantic forms, lexicon, and the parser. There are a few debug options that can be enabled by setting the corresponding flags to True, see the foptions variable for details.

Module attributes

foptions

Options for the CCG parser.

Functions

`compose_neural_ccg_node`(lhs, rhs[, ...])	Compose two neural CCG nodes.
`count_nr_execution_steps`(parsings)	Count the number of execution steps from a list of parsing results.
`gen_used_lexicon_entries`(parsings)	Generate a dictionary of used lexicon entries from a list of parsing results.
`parse_linearization_string`(string)	Parse a linearization string (e.g., `/0\1`) into a list of tuples.

Classes

`LinearizationTuple`	A pair of (index, direction) for representing linearization of function arguments.
`NeuralCCG`	The neural CCG grammar and the implementation for parsing.
`NeuralCCGConjGroundingFunction`	A wrapper for the underlying implementation of a conjunction-typed semantic form (e.g., AND).
`NeuralCCGConjSyntaxType`	Data structure for conjunction syntax types.
`NeuralCCGGroundingFunction`	A data structure contains the implementation of a function (for neural CCG semantics).
`NeuralCCGNode`	A node in the Neural CCG parsing tree.
`NeuralCCGSemantics`	We implement the execution result of the current subtree in the following way: For primitive types (syntax.is_value == True), the execution_buffer field is a list containing a single element recording the execution result.
`NeuralCCGSemanticsExecutionBuffer`	A small data structure that contains the execution buffer, partial type, and number of execution steps.
`NeuralCCGSemanticsPartialTypeLex`	A data structure that will be used in representing the semantic type of a partially applied function.
`NeuralCCGSimpleConjFunction`	A simple implementation for conjunction-typed semantics.
`NeuralCCGSyntaxType`	Data structure for neural CCG syntax types.