<prompt> Theha lenaneo la ho khetholla le ho tšoaea puo e khopisang.nan  <response>: Instruction in English: Develop a program to identify and flag offensive language. . Response in English: Offensive language identification is an important task in text analysis for ensuring online safety and promoting healthy discussions. Here is a Python program that can identify and flag offensive language in a given text:pythonimport nltkfrom nltk.corpus import stopwordsfrom nltk.tokenize import word_tokenize load set of offensive words from a filewith openoffensive_words.txt, r as f: offensive_words setf.read.splitlinesdef flag_offensive_languagetext: tokenizing the text into individual words tokenized_text word_tokenizetext converting all words to lowercase for comparison tokenized_text word.lower for word in tokenized_text removing stop words to reduce noise tokenized_text word for word in tokenized_text if word not in stopwords.wordsenglish flagging offensive words present in text for word in tokenized_text: if word in offensive_words: printfOffensive word detected: word example usagetext this is some nice text with no bad wordsflag_offensive_languagetexttext this text contains a very bad wordflag_offensive_languagetextThis program utilizes the stopwords and word_tokenize functions from the nltk library for text preprocessing. The offensive words are loaded from a file named offensive_words.txt, which should contain one offensive word per line. The program tokenizes the input text, converts all words to lowercase, removes stop words, and then checks if any word in the tokenized text is present in the set of offensive words. If an offensive word is found, it is flagged and printed.This is a basic implementation and can be improved upon by using advanced techniques such as natural language processing or machine learning to better detect offensive language, which may not necessarily be included in a static list. . Response in Sesotho: Ho tsebahatsa puo e khopisang ke mosebetsi oa bohlokoa tlhahlobong ea mongolo bakeng sa ho netefatsa polokeho ea inthanete le ho khothaletsa lipuisano tse phetseng hantle. Mona ke lenaneo la Python le ka khethollang le ho tšoaea puo e khopisang ka mongolo o fanoeng: python import nltk from nltk.corpus import stopwords ho tloha nltk.tokenize import word_tokenize load set of queen words from file with openoffensive_words. txt, r as f: offensive_words setf.read.splitlines def flag_offensive_languagemongolo: tokenizing mongolo hore e be mantsoe a ikemetseng tokenized_text word_tokenizetext ho fetolela mantsoe ohle ho ba litlhaku tse tlase bakeng sa comparison tokenized_text lentsoe.tlase bakeng sa lentsoe le tokenized_text ho tlosa mantsoe a emisang ho fokotsa lerata tokenized_text lentsoe ka lentsoe le ngotsoeng ka tokenized_text haeba lentsoe le se ka li-stopwords.wordsenglish ho tšoaea mantsoe a khopisang a teng mongolong oa lentsoe ka tokenized_text: haeba lentsoe ka mantsoe a khopisang: hatisafLentsoe le khopisang le lemohuoe: word mohlala oa tšebeliso ea mongolo ena ke mongolo o monate o se nang mantsoe a mabe mongolo_o khopisangmongolo sengolo sena se na le mantsoe a mangata lentsoe le lebe flag_offensive_languagetext Lenaneo lena le sebelisa li-stopwords le li-word_tokenize mesebetsi ho tsoa laebraring ea nltk bakeng sa ho lokisa mongolo. Mantsoe a khopisa a tsoa faeleng e bitsoang offensive_words.txt, e tlamehang ho ba le lentsoe le le leng le khopisang mola o mong le o mong. Lenaneo le tšoaea mongolo o kentsoeng, le fetolela mantsoe ohle hore e be litlhaku tse nyane, le tlose mantsoe a emisang, ebe le hlahloba hore na ho na le lentsoe le hlahang mongolong oa tokenized le teng sehlopheng sa mantsoe a khopisang. Haeba lentsoe le khopisang le fumanoa, le tšoauoa me le hatisoe. Ena ke tsebetsong ea mantlha, me e ka ntlafatsoa ka ho sebelisa mekhoa e tsoetseng pele joalo ka puo ea tlhaho kapa ho ithuta ka mochini ho lemoha puo e khopisang hamolemo, e kanna ea se ke ea kenyelletsoa lethathamong le sa fetoheng. 