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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
Import a single file...
Prepare a Corpus (Corpus Builder)
Open an existing project
Settings
Automatic and Customized Settings
Dictionary Building
Co-occurrence Analysis
Word Associations
Co-Word Analysis and Concept Mapping
Comparison between Word pairs
Sequence and Network Analysis
Concordances
Thematic Analysis
Thematic Analysis of Elementary Contexts
Modeling of Emerging Themes
Thematic Document Classification
Dictionary-Based Classification
Key Contexts of Thematic Words
Comparative Analysis
Specificity Analysis
Correspondence Analysis
Multiple Correspondence Analysis
Cluster Analysis
Singular Value Decomposition
Lexical Tools
Text Screening / Disambiguations
Corpus Vocabulary
Stop-Word List
Multi-Word List
Word Segmentation
Other Tools
Variable Manager
Advanced Corpus Search
Contingency Tables
Editor
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
Graph Maker
Homograph
IDnumber
Isotopy
Key-Word (Key-Term)
Lemmatization
Lexical Unit
Lexie and Lexicalization
Markov Chain
MDS
Multiwords
N-grams
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
Bibliography
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).


N.B.:
- 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;
- sometimes, in order to differentiate homographs,
T-LAB adds the underscore ('_') character to their lemma.