tokenSpan

A token span is a contiguous sequence of tokens within a larger text. In natural language processing and computational linguistics, texts are often broken down into individual units called tokens, which can be words, punctuation marks, or even sub-word units. A token span then refers to a specific range of these tokens, typically identified by their starting and ending positions.

For example, in the sentence "The quick brown fox jumps over the lazy dog.", if the tokens are individual words, the token span representing "brown fox" would start at the third token ("brown") and end at the fourth token ("fox"). Token spans are fundamental for many NLP tasks. They are used to mark entities in Named Entity Recognition (NER), where a span might represent a person's name, a location, or an organization.

In question answering systems, a token span can indicate the precise segment of a document that answers a given question. Similarly, in text summarization, token spans might highlight important phrases or sentences to be included in a summary. The concept is also relevant in tasks like relation extraction, where spans might represent the entities involved in a particular relationship, and in coreference resolution, where spans can identify mentions of the same real-world entity. The precise definition and implementation of a token span can vary depending on the tokenization scheme used and the specific NLP library or framework.