LLinguaLab

Research Planner

Choose the next step in your research workflow.

Navigate your research journey—from understanding your data to AI guidance, linguistic analysis, interpretation, and publication-ready reporting.

Data source: Standalone input — current project data will not be changed

INTERACTIVE EXPLORATION

From Language to Application

Choose an example, then reveal its relationships progressively. An application is not an algorithm, and a research path contributes a bounded component rather than a complete product.

WHAT DO I ANALYZE IN LANGUAGE?

Linguistic Research Paths

What do I analyze in language?

LinguaLab is an AI-supported research workspace for computational linguistics.

Deterministic tools perform the available analyses. AI supports guidance, study design, interpretation, reporting, and research assistance.

Corpus Linguistics

What is this path?
An applied workflow for building and checking a corpus, analyzing frequency, contexts, and n-grams, then interpreting findings and preparing a research report. Prepare the corpus → check corpus readiness → analyze frequency → examine contexts → extract n-grams → review patterns → interpret findings → prepare the research report.
Research question
Which words, expressions, and sequences characterize this corpus?
Data needed
A text or a collection of texts suitable for comparison and pattern counting.

Why this path?

Problem: recurring language patterns in a collection → Capability: corpus evidence

What must the computer represent or identify? represent texts and compare counts and contexts

pattern reportscomparative studieslexical evidence

Boundary: does not establish meaning or importance from a count alone

See how a linguistic phenomenon becomes a computational task

Choose an example, then reveal its relationships step by step. This is an educational representation, not an algorithm design or analysis execution.

Smart Path Advisor

Ask about this path, its data, representations, computational tasks, and boundaries.

Contextual guidance does not run an analysis or make the research decision for the researcher.
Start the Corpus Linguistics workflow Continue this path in Analyze

Coming next

  • Collocations
  • Keyword Analysis
  • Corpus Comparison
Expected output
Frequency tables, contextual examples, and recurring sequences.
Report
A corpus-pattern report supported by observed counts and contexts.
Beginner guide

Use this path when you want to discover what repeatedly appears in a body of text. Example: Which expressions recur in university mission statements?

Advanced details

Frequency normalization, concordance interpretation, phrase patterns, and comparative corpus design.

Morphology & Syntax

What is this path?
Examine grammatical categories and structural patterns in text.
Research question
Which grammatical categories are prominent in the selected text?
Data needed
Text suitable for part-of-speech inspection.

Why this path?

Problem: word structure and grammatical relations → Capability: morphology and syntax

What must the computer represent or identify? identify features and relations

grammar-checking componentssearch supportlanguage learning

Boundary: does not by itself create a grammar checker

See how a linguistic phenomenon becomes a computational task

Choose an example, then reveal its relationships step by step. This is an educational representation, not an algorithm design or analysis execution.

Smart Path Advisor

Ask about this path, its data, representations, computational tasks, and boundaries.

Contextual guidance does not run an analysis or make the research decision for the researcher.

Coming next

  • Advanced Parsing
Expected output
An initial view of part-of-speech patterns.
Report
A grammatical-distribution report when analyzable results are available.
Beginner guide

Use this path to ask how words function grammatically. Example: Which parts of speech dominate a news sample?

Advanced details

POS distributions, morphological features, syntactic dependencies, and cross-text structural comparison.

Semantics

What is this path?
Investigate meaning, conceptual relationships, and semantic variation in language data.
Research question
How are meanings and concepts related across the selected texts?
Data needed
Texts selected for a clearly defined meaning-focused comparison.

Why this path?

Problem: meaning relationships and variation → Capability: semantic analysis

What must the computer represent or identify? represent and compare stated meanings

meaning studiesconcept comparisonretrieval support

Boundary: does not settle interpretation without research evidence

See how a linguistic phenomenon becomes a computational task

Choose an example, then reveal its relationships step by step. This is an educational representation, not an algorithm design or analysis execution.

Smart Path Advisor

Ask about this path, its data, representations, computational tasks, and boundaries.

Contextual guidance does not run an analysis or make the research decision for the researcher.

Coming next

  • Embeddings
  • Topic Modeling
  • Clustering validation
Expected output
Meaning relationships or semantic groupings derived from supported analysis.
Report
A semantic-pattern report once dedicated analysis is available.
Beginner guide

Use this path when the question is about meaning rather than word counts. Example: Which concepts occur in similar contexts?

Advanced details

Vector representations, semantic similarity, topic models, and clustering validation.

Discourse & Pragmatics

What is this path?
Study how meaning, stance, and organization emerge beyond individual words and sentences.
Research question
How does a text frame positions and organize meaning for its audience?
Data needed
Complete texts with relevant genre, speaker, or situational context.

Why this path?

Problem: meaning and stance in context → Capability: discourse and pragmatic analysis

What must the computer represent or identify? organize textual and contextual evidence

framing studiesinterpretive reportsannotation designs

Boundary: does not replace contextual scholarly interpretation

See how a linguistic phenomenon becomes a computational task

Choose an example, then reveal its relationships step by step. This is an educational representation, not an algorithm design or analysis execution.

Smart Path Advisor

Ask about this path, its data, representations, computational tasks, and boundaries.

Contextual guidance does not run an analysis or make the research decision for the researcher.

Coming next

  • Discourse Patterns
  • Framing
  • Cohesion / Coherence indicators
Expected output
Evidence-based discourse observations tied to the source texts.
Report
A discourse interpretation report when dedicated evidence is available.
Beginner guide

Use this path to study how language works in context. Example: How do editorials frame responsibility?

Advanced details

Stance, framing, discourse relations, cohesion, coherence, and context-sensitive interpretation.

03 · RESEARCH WORKFLOW

Build Your Study

How do I design and complete the research study?

Move through a concise research workflow. Each step remains optional and should follow the needs of the question and available evidence.

  1. 01Research AdvisorDefine the study ↗
  2. 02Recommended path and research assistantDevelop the plan ↗
  3. 03Analysis with LinguaLab toolsRun analysis ↗
  4. 04InterpretationInterpret results
  5. 05Research ReportPrepare the report
  6. 06Writing supportOpen writing support ↗
Choose your starting point
  • Start with a linguistic path if you know the linguistic phenomenon you want to study.
  • Start with computational workflows if you already know the NLP or data task.
  • Start with the Research Advisor if you are unsure.
  • After analysis, continue to interpretation, reporting, and writing support.