lemmatizátory

A lemmatizer is a natural language processing tool that reduces inflected or derived words to their base or dictionary form, known as the lemma. This process, called lemmatization, differs from stemming, which often chops off word endings without considering the word's meaning or morphological analysis. Lemmatization aims to return the canonical form of a word, which is typically its lemma found in a lexicon. For example, a lemmatizer would reduce "running," "ran," and "runs" to the lemma "run." Similarly, "better" would be lemmatized to "good."

The effectiveness of a lemmatizer depends on its ability to understand the context of a word and its part of speech. Without this contextual information, lemmatization can be ambiguous. Many lemmatizers employ techniques such as morphological analysis, part-of-speech tagging, and dictionaries or wordnets to achieve accurate results. Lemmatizers are crucial components in various natural language processing applications, including information retrieval, text summarization, machine translation, and sentiment analysis, as they help to normalize text data and improve the performance of these systems by treating different forms of the same word as equivalent.