👉 Dependence engineering is a technique used in natural language processing (NLP) to manipulate the relationships between words or phrases within a sentence, thereby influencing how these elements are interpreted by machine learning models. It involves creating or altering syntactic dependencies, such as subject-verb or noun-modifier relationships, to guide the model in understanding and generating text more accurately. By strategically adjusting these dependencies, engineers can improve model performance on tasks like machine translation, sentiment analysis, and question answering, especially in languages with complex grammatical structures. This approach allows for more nuanced and context-aware language processing, enhancing the model's ability to capture the intended meaning and generate coherent, contextually relevant outputs.
