Topic Modelling

Sentiment Analysis

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

Text Classification

The task of assigning predefined categories or labels to text documents based on their content.

Text Summarisation

The process of creating a concise and coherent summary of a longer text document while preserving key information.

Abstractive Summarisation

A text summarisation approach that generates novel sentences to capture the essential meaning of a document, rather than simply extracting and rearranging existing sentences.

Aspect-Based Sentiment Analysis

A fine-grained sentiment analysis approach that identifies opinions directed at specific aspects or features of an entity, such as a product's price, quality, or design.

The task of identifying all expressions in text that refer to the same real-world entity.

A language model trained on text from dozens or hundreds of languages simultaneously, enabling cross-lingual understanding and generation without language-specific fine-tuning.

The capability of language models to accurately interpret and execute natural language instructions, a core skill developed through instruction tuning and alignment training.

A neural network trained on massive text corpora that can generate, understand, and reason about natural language.

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

Bidirectional Encoder Representations from Transformers — a language model that understands context by reading text in both directions.

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

The maximum amount of text a language model can consider at once when generating a response.