From ChatGPT: In the context of Natural Language Processing (NLP), a “span” typically refers to a sequence of consecutive tokens in a text or document. A token is a unit of text that has been extracted from the input text during the tokenization process, which involves breaking down a piece of text into individual words, punctuation marks, or other meaningful elements.
So, a span in NLP is essentially a contiguous sequence of these tokens. It can represent entities, phrases, or any other segment of text that is relevant to the analysis or task at hand. Spans are commonly used in tasks such as named entity recognition (NER), sentiment analysis, and information extraction, where identifying and analyzing specific portions of text is essential.
For example, in the sentence “John Smith works at XYZ Corporation,” a span might be “John Smith” if the task is named entity recognition, or it could be “works at XYZ Corporation” if the task is extracting job information.