Expressionsthat

Expressionsthat is not a standard term in linguistics or computer science. In practice, it refers to a tokenization artifact where the two-word sequence expressions that is, or expressions that, is concatenated into a single token. Such tokens commonly appear in raw text, optical character recognition outputs, scraped data, or informal writing, and they can hinder downstream processing.

In natural language processing and text mining, expressionsthat-type tokens pose challenges for parsing, search, and annotation. They may be misinterpreted as proper nouns, domain-specific terms, or unfamiliar vocabulary, reducing the accuracy of part-of-speech tagging, named-entity recognition, and syntactic parsing. Solutions focus on de-tokenization and normalization, including rule-based post-processing, dictionary lookups, and subword models. Modern approaches often rely on subword tokenization (for example, byte-pair encoding) or machine-learned de-tokenizers to recover the intended two-word sequence.

From a linguistic perspective, the sequence expressions that frequently appears as a single token often introduces relative clauses or descriptive phrases, as in “expressions that describe…” The meaning is derived from the surrounding context, not from the concatenated form itself. Recognizing and correcting such tokens improves readability, search relevance, and data quality.

See also: tokenization, de-tokenization, normalization, multiword expressions, natural language processing.