Information Extraction

Byte-Pair Encoding

A subword tokenisation algorithm that iteratively merges the most frequent character pairs to build a vocabulary.

Named Entity Recognition

An NLP task that identifies and classifies named entities in text into categories like person, organisation, and location.

Dependency Parsing

The syntactic analysis of a sentence to establish relationships between head words and words that modify them.

Part-of-Speech Tagging

The process of assigning grammatical categories (noun, verb, adjective) to each word in a text.

Coreference Resolution

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

Relation Extraction

Identifying semantic relationships between entities mentioned in text.

A probabilistic model that assigns probabilities to sequences of words, enabling prediction of the next word in a sequence.

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

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

A measure of how closely the meanings of two text passages align, computed through embedding comparison and used in duplicate detection, search, and recommendation systems.

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

Global Vectors for Word Representation — an unsupervised learning algorithm for obtaining word vector representations from aggregated word co-occurrence statistics.

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

Connecting language model outputs to real-world knowledge, facts, or data sources to improve factual accuracy.