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Verb Valency Reader

This module includes classes and functions for reading the Persian Verb Valency Lexicon.

The Persian Verb Valency Lexicon is a collection containing valency information for more than 4,500 Persian verbs. This lexicon specifies obligatory and optional complements for various types of verbs: simple, compound, prefixed, and phrasal verbs. The high frequency of compound verbs in Persian doubles the need for a verb valency lexicon, as identifying compound verbs is more difficult than identifying simple ones for both humans and machines. Providing a list of verbs (including compound verbs) along with their valency structures is a significant help for NLP tasks. Furthermore, based on Dependency Theory, the fundamental structure of a sentence can be derived from the verb's valency, which adds to the importance of knowing these structures in linguistic texts.

Verb

Bases: NamedTuple

A named tuple representing a Persian verb and its valency properties.

Attributes:

Name Type Description
past_light_verb str

The past light verb.

present_light_verb str

The present light verb.

prefix str

The verb prefix.

nonverbal_element str

The non-verbal element of a compound verb.

preposition str

The associated preposition.

valency str

The valency structure of the verb.

VerbValencyReader

This class includes functions for reading the Persian Verb Valency Lexicon.

Parameters:

Name Type Description Default
valency_file str

Path to the lexicon file.

'valency.txt'

__init__(valency_file='valency.txt')

Initializes the VerbValencyReader.

Parameters:

Name Type Description Default
valency_file str

Path to the lexicon file. Defaults to "valency.txt".

'valency.txt'

verbs()

Iterates through the verbs in the lexicon.

Yields:

Type Description
Verb

The next verb in the lexicon as a Verb object.