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T-LAB
Introduction
What T-LAB does and what it enables us to do
Requirements and Performances
Corpus Preparation
Corpus Preparation
Structural Criteria
Formal Criteria
File
New Corpus
Gather your Texts
Open Corpus
Settings
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Co-occurrence Analysis
Word Associations
Co-Word Analysis and Concept Mapping
Comparison between Word pairs
Sequence Analysis
Concordances
Thematic Analysis
Thematic Analysis of Elementary Contexts
Modeling of Emerging Themes
Sequences of Themes
Key Contexts of Thematic Words
Thematic Document Classification
Comparative Analysis
Specificity Analysis
Correspondence Analysis
Multiple Correspondence Analysis
Cluster Analysis
Contingency Tables
Lexical Tools
Stop-Word List
Multi-Word List
Corpus Vocabulary
Disambiguation
Dictionary Building
Utilities
Editor
Memo
Variable Manager
Create a Sub-Corpus
Glossary
Analysis Unit
Association Indexes
Chi-Square
Cluster Analysis
Coding
Context Unit
Corpus and Subsets
Correspondence Analysis
Data Table
Disambiguation
Dictionary
Elementary Context
Frequency Threshold
GraphML
Homograph
IDnumber
Isotopy
Key-Word (Key-Term)
Lemmatization
Lexical Unit
Lexie and Lexicalization
Markov Chain
MDS
Multiwords
Naïve Bayes
Normalization
Occurrences and Co-occurrences
Poles of Factors
Primary Document
Profile
Specificity
Stop Word List
Test Value
Thematic Nucleus
TF-IDF
Variables and Categories
Words and Lemmas
Bibliografia
www.tlab.it

Lemmatization


Lemmatization involves the reduction of corpus words to their respective headwords (i.e. lemmas). In the linguistic dictionaries that we may consult, every entry corresponds to a lemma that - generally - defines a set of words with the same lexical root (or lexeme) and that belongs to the same grammatical category (verb, adjective, etc.).

As a rule, lemmatization entails that verb forms are taken back to the base form, nouns to the singular form, and so on.

For example, the inflected forms "speaks" and "speaking", resulting from a combination of a sole root with two different suffixes (<-s> and <-ing>), are brought back to the same lemma "speak". There are, however, some cases in which the lemmatization doesn't observe the rule of the common root; particularly in the case of many irregular verbs.

During the corpus importation phase, T-LAB carries out a specific kind of automatic lemmatization, that follows the logic of the following "tree".

Obviously, the reference dictionary is the one implemented in T-LAB.

The abbreviations of the four-categories are used in many tables, always in the "INF" column (or field).


In particular, the "DIS" category ("to distinguish") means that T-LAB does not apply the standard lemmatization, in order to avoid annulling the significant meanings among the different forms.