Natural Language Processing (NLP)
The field of getting computers to understand and generate human language — the decades-old discipline whose task-specific methods collapsed, in a few years, into a single general model.
Reviewed July 16, 2026Stable
When not to use it
- As a synonym for large language models. NLP is the field; an LLM is the current technology within it, not the whole discipline.
- For tasks better framed as pure information retrieval or structured-data queries, where language modeling adds cost without benefit.
- When a simple deterministic method (a regex, a lookup) solves the problem, reaching for a language model is overkill.
Reach for something else instead
- Computational linguistics overlaps heavily but leans toward the scientific study of language rather than building applications.
- Information retrieval handles finding relevant documents, a related but distinct problem from understanding their content.
- Speech processing covers the audio side, often treated alongside NLP once speech is transcribed to text.
Sources & further reading
- Jurafsky & Martin, Speech and Language Processing — the standard textbook covering the field's tasks and history.
- Vaswani et al. (2017), Attention Is All You Need — the transformer that reshaped NLP into the language-model era.
- Devlin et al. (2019), BERT — pretraining that made one model transferable across many NLP tasks.
Primary sources, listed so you can check the claims on this page rather than take them on trust.
Where people go wrong
- Treating high benchmark scores as proof that language is understood or that NLP is solved.
- Assuming progress in English transfers to other languages; low-resource languages lag far behind.
- Forgetting the task vocabulary once one model does everything, which leaves you unable to specify or evaluate what you actually want.
At a glance
FieldLanguage & LLMs
Scopeunderstanding and generating human language
Erasrules → statistical → deep learning → transformers/LLMs
Defining shiftmany methods into one model
DifficultyBeginner → Intermediate