# natural language processing

> field of computer science and linguistics

**Wikidata**: [Q30642](https://www.wikidata.org/wiki/Q30642)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Natural_language_processing)  
**Source**: https://4ort.xyz/entity/natural-language-processing

## Summary
Natural language processing (NLP) is a field of computer science, artificial intelligence, and linguistics focused on enabling computers to understand, interpret, and generate human language. It combines computational linguistics with statistical, machine learning, and deep learning models. The goal of NLP is to bridge the communication gap between humans and computers by processing and analyzing large amounts of natural language data.

## Key Facts
*   **Classification:** NLP is a subfield of artificial intelligence, computer science, and computational linguistics.
*   **Scope:** It is recognized as an academic discipline, a field of study, an industry, and a branch of linguistics.
*   **Common Acronym:** The field is widely known by the acronym NLP. Other short names include TAL, TALN, and PLN.
*   **Core Focus:** NLP is the study of numerous tasks, including machine translation, sentiment analysis, speech recognition, part-of-speech tagging, parsing, and natural language generation.
*   **Key Subfields:** Major sub-topics within NLP include natural language understanding (NLU) and natural language generation (NLG).
*   **Practitioners:** Professionals who work in this field are known as natural language processing engineers.
*   **Related Technologies:** NLP is the core technology behind dialogue systems, question answering systems, automatic summarization, and information extraction.

## FAQs
### Q: What is natural language processing (NLP)?
A: Natural language processing, or NLP, is a field of artificial intelligence and computer science that deals with how computers can be programmed to process and analyze large amounts of human language data. Its primary goal is to enable machines to understand, interpret, and generate text and speech in a way that is valuable.

### Q: Is NLP a part of artificial intelligence?
A: Yes, natural language processing is a subfield of artificial intelligence. It specifically focuses on the software and methods that allow machines to exhibit intelligent behavior related to understanding and using human language.

### Q: What are some examples of NLP tasks?
A: Common NLP tasks include machine translation (translating text from one language to another), sentiment analysis (identifying subjective information in text), speech recognition (converting spoken language to text), and natural language generation (automatically creating text). Other examples are part-of-speech tagging, named-entity recognition, and automatic summarization.

## Why It Matters
Natural language processing is significant because it solves the fundamental problem of how computers can process and understand unstructured human language. The vast majority of human knowledge is stored as text and speech, and NLP provides the tools to unlock this data for analysis, automation, and interaction. It powers everyday technologies like virtual assistants, machine translation services, customer service chatbots, and spam filters. By enabling computers to comprehend context, sentiment, and intent in human language, NLP has revolutionized how we interact with technology, extract insights from data, and automate tasks that previously required human linguistic expertise.

## Notable For
*   **Interdisciplinary Foundation:** NLP is distinct for its deep integration of computer science, artificial intelligence, and linguistics, combining computational models with the study of language structure and meaning.
*   **Handling Unstructured Data:** It specializes in processing and deriving meaning from unstructured data like text and speech, which is fundamentally different from the structured data found in traditional databases.
*   **Enabling Conversational AI:** NLP is the core technology that makes conversational systems possible, including dialogue systems (chatbots) and question-answering systems that can interact with humans using natural language.
*   **Wide Array of Specialized Tasks:** The field encompasses a broad spectrum of distinct tasks, from foundational processes like tokenization and part-of-speech tagging to complex applications like machine translation, text simplification, and automatic summarization.
*   **Driving Information Extraction:** NLP is central to information extraction, the process of automatically pulling structured information (like names, dates, and relationships) from unstructured documents and human language texts.

## Body
### ### Classification and Scope
Natural language processing is an interdisciplinary field classified as a subclass of **artificial intelligence**, **computer science**, and **computational linguistics**. It is also considered an instance of an **academic discipline**, a **field of study**, an **industry**, and a **branch of linguistics**. The field is practiced by professionals known as **natural language processing engineers**.

### ### Core Tasks and Subfields
NLP encompasses a wide range of tasks and sub-topics aimed at enabling computers to work with human language. These can be broadly categorized:

*   **Understanding and Analysis:**
    *   **Natural Language Understanding (NLU):** A subtopic focused on machine reading comprehension.
    *   **Sentiment Analysis:** Identifying and extracting subjective information.
    *   **Semantic Analysis:** The computational application of concept approximation.
    *   **Part-of-Speech Tagging:** Identifying the grammatical type of words.
    *   **Syntactic Parsing:** Automatic analysis of the syntactic structure of language.
    *   **Named-Entity Recognition:** Identifying and categorizing key information in text.
    *   **Information Extraction:** Automatically extracting structured information from unstructured documents.
    *   **Text Mining:** Analyzing text to extract information.

*   **Language Processing and Manipulation:**
    *   **Tokenization:** Breaking text into chunks for analysis.
    *   **Stemming & Lemmatisation:** Reducing words to their root form.
    *   **Text Segmentation:** Dividing text into meaningful units like sentences or topics.
    *   **Text Simplification:** An automated process to make text easier to understand.

*   **Generation and Interaction:**
    *   **Natural Language Generation (NLG):** Automatically generating text from data.
    *   **Machine Translation:** Using software for language translation.
    *   **Automatic Summarization:** Creating a shortened version of a text.
    *   **Dialogue Systems:** Computer systems designed to converse with a human.
    *   **Question Answering:** A research area focused on building systems that can answer questions posed in natural language.

*   **Speech-Related Tasks:**
    *   **Speech Recognition:** Automatic conversion of spoken language into text.
    *   **Speaker Verification:** Verifying the identity of a speaker.

### ### Terminology and Identifiers
*   **Short Names:** NLP, TAL, TALN, PLN, PIN
*   **Aliases:** procesamiento del lenguaje natural, traitement du langage naturel, ingénierie linguistique
*   **Hashtag:** #NLProc
*   **GitHub Topics:** `natural-language-processing`, `nlp`
*   **Subreddit:** r/LanguageTechnology

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## References

1. Medical Subject Headings
2. [Source](https://id.ndl.go.jp/auth/ndlsh/00562347)
3. [Source](https://www.clarin.eu/glossary)
4. UMLS 2023
5. [Source](https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/1297.02008?OpenDocument)
6. National Library of Israel
7. [Source](https://vocabs.dariah.eu/tadirah/naturalLanguageProcessing)
8. [OpenAlex](https://docs.openalex.org/download-snapshot/snapshot-data-format)