<prompt> Fana ka mehlala e mene ea mesebetsi ea puo ea tlhahonan  <response>: Instruction in English: Give four examples of natural language processing tasks . Response in English: 1. Sentiment Analysis: This task involves analyzing text data in order to determine the emotion, tone, or opinion conveyed. For example, it can be used to determine whether product reviews are positive, negative, or neutral.2. Speech Recognition: This task involves converting spoken words into written text, which is commonly used for voice-activated assistants, speech-to-text dictation software, and in automated phone systems.3. Text Classification: This task involves assigning categories, labels or tags to text data. Some common applications of text classification include email spam filtering and news article categorization, where news articles are automatically classified into various topics such as finance, sports or politics, etc.4. Named Entity Recognition: This task involves identifying and extracting certain specific types of information from unstructured text, such as names of people, organizations, locations, dates, and other types of entities that can commonly occur within text. It is commonly used in various applications such as chatbots, social media monitoring, and automated data extraction. . Response in Sesotho: 1. Tlhahlobo ea Maikutlo: Mosebetsi ona o kenyelletsa ho sekaseka lintlha tsa mongolo e le ho fumana maikutlo, molumo, kapa maikutlo a fetisoang. Ka mohlala, e ka sebelisoa ho fumana hore na maikutlo a lihlahisoa a nepahetse, a fosahetse, kapa a sa nke lehlakore. 2. Tlhokomeliso ea Puo: Mosebetsi ona o kenyelletsa ho fetolela mantsoe a buuoang hore e be mongolo o ngotsoeng, oo hangata o sebelisoang bakeng sa bathusi ba nang le lentsoe, software ea ho bua ho ea ho mongolo, le litsebetsong tse ikemetseng tsa fono. 3. Karolelano ea Lingoliloeng: Mosebetsi ona o kenyelletsa ho abela likarolo, lileibole kapa li-tag ho data ea mongolo. Tse ling tsa litsebetso tse tloaelehileng tsa ho hlopha mongolo li kenyelletsa ho sefa li-spam tsa lengolo-tsoibila le ho arola lingoliloeng tsa litaba, moo lihlooho tsa litaba li aroloang ka lihlooho tse fapaneng tse kang tsa lichelete, lipapali kapa lipolotiki, joalo-joalo. lintlha tse tsoang ho mongolo o sa hlophisoang, joalo ka mabitso a batho, mekhatlo, libaka, matsatsi, le mefuta e meng ea mekhatlo e ka hlahang hangata ka hara mongolo. E sebelisoa hangata litsebetsong tse fapaneng tse kang li-chatbots, tlhahlobo ea litaba tsa sechaba, le ho ntša data ka boiketsetso. 