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-Shot+Named+Entity+Recognition%252C+Exploiting+the+Power+of+Large+Language+Models%26subtitle%3dLarge+language+models+(LLMs)+allow+us+to+generate+high-quality+human-like+text.+One+interesting+task+in+natural+language+processing+(NLP)+is+named+entity+recognition+(NER)%252C+which+seeks+to+detect+mentions+of+relevant+information+in+documents.+This+paper+presents+llmNER%252C+a+Python+library+for+implementing+zero-shot+and+few-shot+NER+with+LLMs%253B+by+providing+an+easy-to-use+interface%252C+llmNER+can+compose+prompts%252C+query+the+model%252C+and+parse+the+completion+returned+by+the+LLM.+Also%252C+the+library+enables+the+user+to+perform+prompt+engineering+efficiently+by+providing+a+simple+interface+to+test+multiple+variables.+We+validated+our+software+on+two+NER+tasks+to+show+the+library%27s+flexibility.+llmNER+aims+to+push+the+boundaries+of+in-context+learning+research+by+removing+the+barrier+of+the+prompting+and+parsing+steps.&cdnurl=https%3a%2f%2fbing.ai.mrmusic.cloudns.ch/th%2fth%2fid%2fR.83f86a6e6b47ccb3e305b98b9604bf4e%3frik%3dPSKP4M0hUm6MgA%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Large+Language+Model+Named+Entity+Recognition&FORM=IRPRST&ck=FC52A397BBBFB66815927B68F55F8FBF&selectedIndex=1&itb=0)
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