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A modular view of sentence processing assumes that each factor involved in sentence processing is computed in its own module, which has limited means of communication with the other modules. For example, syntactic analysis creation takes place without input from semantic analysis or context-dependent information, which are processed separately.
It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a ...
A notable example of deep semantic annotation is the Groningen Meaning Bank, developed at the University of Groningen and annotated using Discourse Representation Theory. An example of a shallow semantic treebank is PropBank, which provides annotation of verbal propositions and their arguments, without attempting to represent every word in the ...
In linguistics, Immediate Constituent Analysis (ICA) is a syntactic theory which focuses on the hierarchical structure of sentences by isolating and identifying the constituents. While the idea of breaking down sentences into smaller components can be traced back to early psychological and linguistic theories, ICA as a formal method was ...
Syntactic parsing is one of the important tasks in computational linguistics and natural language processing, and has been a subject of research since the mid-20th century with the advent of computers. Different theories of grammar propose different formalisms for describing the syntactic structure of sentences.
In sentence processing, the predictability of a word is established by two related factors: 'cloze probability' and 'sentential constraint'. Cloze probability reflects the expectancy of a target word given the context of the sentence, which is determined by the percentage of individuals who supply the word when completing a sentence whose final ...
Typical level-of-processing theory would predict that picture encodings would create deeper processing than lexical encoding. "Memory over the short term and the long term has been thought to differ in many ways in terms of capacity, the underlying neural substrates, and the types of processes that support performance." [13]
Bottom-up information processing Students learn partially through bottom-up information processing, or processing based on information present in the language presented. For example, in reading bottom-up processing involves understanding letters, words, and sentence structure rather than making use of the students’ previous knowledge ...