Pith. sign in

REVIEW 1 cited by

Subjective Assessment of Text Complexity: A Dataset for German Language

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1904.07733 v1 pith:OQF5PJLU submitted 2019-04-16 cs.CL

Subjective Assessment of Text Complexity: A Dataset for German Language

classification cs.CL
keywords germansubjectiveassessmentdatasetlanguagesentencesdifferentprovided
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

This paper presents TextComplexityDE, a dataset consisting of 1000 sentences in German language taken from 23 Wikipedia articles in 3 different article-genres to be used for developing text-complexity predictor models and automatic text simplification in German language. The dataset includes subjective assessment of different text-complexity aspects provided by German learners in level A and B. In addition, it contains manual simplification of 250 of those sentences provided by native speakers and subjective assessment of the simplified sentences by participants from the target group. The subjective ratings were collected using both laboratory studies and crowdsourcing approach.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. From Multimodal Signals to Adaptive XR Experiences for De-escalation Training

    cs.HC 2026-04 unverdicted novelty 4.0

    An early multimodal XR prototype fuses five signal streams with an interpretation layer to detect escalation cues and enable adaptive de-escalation training.