Lemmatisation (or lemmatization) in linguistics is the process of grouping together the inflected forms of a word so they can be analysed as a single item, identified by the word's lemma, or dictionary form.
In many languages, words appear in several inflected forms. For example, in English, the verb 'to walk' may appear as 'walk', 'walked', 'walks' or 'walking'. The base form, 'walk', that one might look up in a dictionary, is called the lemma for the word. The association of the base form with a part of speech is often called a lexeme of the word.
Lemmatisation is closely related to stemming. The difference is that a stemmer operates on a single word without knowledge of the context, and therefore cannot discriminate between words which have different meanings depending on part of speech. However, stemmers are typically easier to implement and run faster. The reduced "accuracy" may not matter for some applications. In fact, when used within information retrieval systems, stemming improves query recall accuracy, or true positive rate, when compared to lemmatisation. Nonetheless, stemming reduces precision, or the proportion of positively-labeled instances that are actually positive, for such systems.
- The word "better" has "good" as its lemma. This link is missed by stemming, as it requires a dictionary look-up.
- The word "walk" is the base form for the word "walking", and hence this is matched in both stemming and lemmatisation.
- The word "meeting" can be either the base form of a noun or a form of a verb ("to meet") depending on the context; e.g., "in our last meeting" or "We are meeting again tomorrow". Unlike stemming, lemmatisation attempts to select the correct lemma depending on the context.
Lemmatization has been put in place in our algorithms so you have nothing to do.
Every time you train your bot, all the inflected forms of this word will be understood as well.
Updated 2 days ago