Textzuständen

Textzuständen describe representations of text at different stages of processing in computing and linguistics. Each Zustand is a snapshot of the data, capturing aspects such as encoding, normalization, tokenization, and annotations. The concept supports modular design, reproducibility, and clear data provenance by making transformations between stages explicit.

Typical textzustände include: Raw text as received from a source; Normalized text with consistent encoding, case folding, diacritics handling, and whitespace standardization; Tokenized text divided into tokens or words; Lemmatized or stemmed forms for canonical word representations; Part-of-speech tagged text; Named-entity annotated text; Syntactically parsed text; and higher-level semantic or discourse representations. In information retrieval, an additional indexed state stores features suitable for efficient search.

Transitions between states are produced by processing pipelines. Finite-state methods and text-processing tools are often used to move from one Zustand to another, for example in tokenization, normalization, stemming, or POS tagging. States are commonly serialized in standard formats such as CoNLL, JSON, or XML-based schemas, sometimes aligned with domain-specific formats like TEI for scholarly texts.

Applications and benefits: using defined textzustände enables modular, reusable pipelines, facilitates debugging and reproducibility, and supports caching and incremental processing. It also helps in multilingual and cross-domain settings, where different languages or tasks may require tailored state schemas.

See also: natural language processing pipeline, text normalization, tokenization, lemmatization, part-of-speech tagging, named-entity recognition, finite-state transducers.