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TextDescriptives: A Python package for calculating a large variety of metrics from text

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arxiv 2301.02057 v3 pith:H3DL7C5I submitted 2023-01-05 cs.CL

Lasse Hansen , Ludvig Renbo Olsen , Kenneth Enevoldsen This is my paper · ORCID
classification cs.CL
keywords packageanalysingcalculatingfeatureslargelinguisticmetricspython
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TextDescriptives is a Python package for calculating a large variety of metrics from text. It is built on top of spaCy and can be easily integrated into existing workflows. The package has already been used for analysing the linguistic stability of clinical texts, creating features for predicting neuropsychiatric conditions, and analysing linguistic goals of primary school students. This paper describes the package and its features.

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  1. Alignment Drift in CEFR-prompted LLMs for Interactive Spanish Tutoring

    cs.CL 2025-05 conditional novelty 5.0 of 10

    CEFR-based system prompts initially control Spanish text difficulty in simulated tutoring dialogues, but the effect weakens over nine turns across four open-source LLMs.

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