A robust discussion persists within the technical and academic communities about the suitability of LLMs for tasks like Named Entity Recognition (NER). While LLMs have demonstrated extraordinary capabilities across a wide range of language-related tasks, several...
On November 19, the Beyond Search Web log published a brief analysis of our multilingual NER (Named Entity Recognition system) technology. The post highlighted the challenges of handling Chinese personal names in English to enable accurate and consistent...
Getting GPT to Answer Consistently and with Style GPT, like other generative models, tends to provide disparate answers for the same question. Sometimes answers vary only slightly, but sometimes they are very inconsistent or even contradictory. Behavior of Standard...
Technological Alchemy: Using GPT in CX According to Blake Morgan, a CX expert, ChatGPT has major flaws that prevent it from becoming a useful tool in industries like Customer Experience. In, Cons Of ChatGPT For Customer Experience, an article recently published in...
For Consistent LLM Answers, Fine-tune with Examples. LOTS of Examples LLMs tend to be very creative and introduce diversity and creativity in answers. That’s good for certain types of questions like: What can you tell me about La Cibeles? What gothic buildings should...
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