All these methods heavily rely on numerous carefully hand-engineered features such as lexical (bag-of-words (BOW)), semantic (hypernyms, synonyms), structural (part of speech (POS) tags, lemmas, orthographic shapes, headings), statistical (statistical distributions of token types) and sequential (sentence position, surrounding features, predicted labels) features.
current emerging artificial neural network (ANN) based models have removed the need for manually selected features; instead, features are self-learned from the token and/or character embeddings.