Semantilise

Semantilise is a term that combines "semantic" and "neutralise," referring to the process of removing or minimizing the emotional or subjective elements from a piece of text, making it more objective and factual. This process is often used in fields such as data analysis, machine learning, and natural language processing, where the focus is on the underlying meaning rather than the emotional tone or stylistic elements of the text.

The semantilisation of text can involve several techniques, including:

1. Sentiment analysis: Identifying and removing or downplaying words and phrases that convey strong emotions or opinions.

2. Lexical simplification: Replacing complex or ambiguous words with simpler, more straightforward alternatives.

3. Contextual analysis: Ensuring that the remaining words and phrases are used in a way that is consistent with their intended meaning, without any hidden or implied emotional content.

Semantilisation is not the same as removing all emotional content from a text, as some level of subjectivity may be necessary for certain applications. Instead, the goal is to create a version of the text that is more suitable for the specific task at hand, such as improving the accuracy of a machine learning model or making the text more accessible to a wider audience.

In summary, semantilise is a process of making text more objective and factual by removing or minimizing its emotional and subjective elements. This can be achieved through various techniques, and the degree of semantilisation will depend on the specific requirements of the task at hand.