Slot Filling

Natural Language Processing

The field of AI focused on enabling computers to understand, interpret, and generate human language.

Seq2Seq Model

A neural network architecture that maps an input sequence to an output sequence, used in translation and summarisation.

Latent Dirichlet Allocation

A generative probabilistic model for discovering topics in a collection of documents.

Text Embedding

Dense vector representations of text passages that capture semantic meaning for similarity comparison and retrieval.

Semantic Search

Search technology that understands the meaning and intent behind queries rather than just matching keywords.

Vector Database

A database optimised for storing and querying high-dimensional vector embeddings for similarity search.

Constitutional AI

An approach to AI alignment where models are trained to follow a set of principles or constitution.

Natural Language Understanding

The subfield of NLP focused on machine reading comprehension and extracting meaning from text.

Natural Language Generation

The subfield of NLP concerned with producing natural language text from structured data or representations.

Document Understanding

AI systems that extract structured information from unstructured documents by combining optical character recognition, layout analysis, and natural language comprehension.

Cross-Lingual Transfer

The application of models trained in one language to perform tasks in another language, leveraging shared multilingual representations learned during pre-training.

Text Embedding Model

A neural network trained to convert text passages into fixed-dimensional vectors that capture semantic meaning, enabling similarity search, clustering, and retrieval applications.

The process of breaking text into smaller units (tokens) such as words, subwords, or characters for processing by language models.

Techniques and architectures that enable language models to process and reason over extremely long input sequences, from tens of thousands to millions of tokens.

A software application that simulates human conversation through text or voice interactions using NLP.

Generative Pre-trained Transformer — a family of autoregressive language models that generate text by predicting the next token.

A neural network model that learns distributed word representations by predicting surrounding context words.

The computational study of people's opinions, emotions, and attitudes expressed in text.

The process of automatically extracting structured information from unstructured or semi-structured text sources.

An NLP task where a system automatically answers questions posed in natural language based on given context.