The term “Natural Language Processing (NLP)” refers to the automated processing, analysis, and generation of human language by computer systems. The goal is to understand, structure, and leverage text (and - combined with speech modules - spoken language) so that information can be extracted, processes automated, and human - software interaction improved - or example in chatbots, semantic search, document analysis, or translation workflows.
Tokenization & Segmentation: Splitting text into sentences, words, or subwords as the basis for analysis.
Lemmatization/Stemming & Normalization: Reducing words to base forms, spell correction, and unifying variants.
Part-of-Speech Tagging & Parsing: Grammatical labeling and syntactic analysis to structure sentences.
Named Entity Recognition (NER) & Entity Linking: Detecting people, locations, organizations and linking them to knowledge sources.
Intent Detection & Slot Filling: Identifying user intent and key parameters for chatbots and assistants.
Text Classification & Categorization: Automatically assigning texts to topics, labels, or workflows.
Sentiment & Emotion Analysis: Determining attitudes (positive/negative/neutral) and emotions.
Keyword & Topic Extraction (Topic Modeling): Identifying key terms and themes in large corpora.
Summarization (extractive/abstractive): Condensing long documents to their essentials.
Question Answering & Information Extraction: Answering free-form questions and extracting facts, relations, and events.
Machine Translation & Language Identification: Automatic translation between languages and detection of the source language.
Semantic Search & Embeddings: Meaning-based retrieval and vector representations for “similar” content.
Natural Language Generation (NLG): Automatically producing texts such as summaries, answers, or reports.
PII Detection & Anonymization: Identifying personal data and masking it for compliance/privacy.
Speech-adjacent modules (optional): Automatic Speech Recognition (ASR/STT) and Text-to-Speech (TTS) combined with NLP workflows.
A service desk automatically prioritizes and routes incoming emails by topic and urgency.
A chatbot interprets user intent and provides context-aware, high-quality answers.
Legal/Compliance teams extract clauses, deadlines, and risks from contracts.
A company implements semantic search across knowledge bases, manuals, and ticket systems.
Marketing analyzes product reviews and tracks sentiment towards brands and campaigns.
Finance or procurement teams parse invoices/receipts (OCR + NLP) to populate ERP fields.
HR parses résumés, extracts qualifications, and matches candidates to job profiles.
Meeting transcripts are summarized automatically and enriched with action items.