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Topicalization is a mechanism of syntax that establishes an expression as the sentence or clause topic by having it appear at the front of the sentence or clause (as opposed to in a canonical position later in the sentence). This involves a phrasal movement of determiners, prepositions, and verbs to sentence-initial position. [1]
The topic of a sentence is distinct from the grammatical subject. The topic is defined by pragmatic considerations, that is, the context that provides meaning. The grammatical subject is defined by syntax. In any given sentence the topic and grammatical subject may be the same, but they need not be.
The topic (or theme) of a sentence is what is being talked about, and the comment (or rheme, or sometimes focus) is what is being said about the topic. That the information structure of a clause is divided in this way is generally agreed on, but the boundary between topic/theme depends on grammatical theory.
Topic analysis consists of two main tasks: topic identification and text segmentation. While the first is a simple classification of a specific text, the latter case implies that a document may contain multiple topics, and the task of computerized text segmentation may be to discover these topics automatically and segment the text accordingly ...
A sentence diagram is a pictorial representation of the grammatical structure of a sentence. The term "sentence diagram" is used more when teaching written language, where sentences are diagrammed. The model shows the relations between words and the nature of sentence structure and can be used as a tool to help recognize which potential ...
A major sentence is a regular sentence; it has a subject and a predicate, e.g. "I have a ball." In this sentence, one can change the persons, e.g. "We have a ball." However, a minor sentence is an irregular type of sentence that does not contain a main clause, e.g. "Mary!", "Precisely so.", "Next Tuesday evening after it gets dark."
The sentence can be read as "Reginam occidere nolite, timere bonum est, si omnes consentiunt, ego non. Contradico. " ("don't kill the Queen, it is good to be afraid, even if all agree I do not. I object."), or the opposite meaning " Reginam occidere nolite timere, bonum est; si omnes consentiunt ego non contradico.
In statistics and natural language processing, a topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for discovery of hidden semantic structures in a text body.