mlsanityData to 13 Oct 2026

Shallow Discourse Annotation for Chinese TED Talks

arXiv 2003.04032 ↗First posted 9 Mar 2020cs.CLcited by 13

Not on the map. Why?

Abstract (arXiv)

Text corpora annotated with language-related properties are an important resource for the development of Language Technology. The current work contributes a new resource for Chinese Language Technology and for Chinese-English translation, in the form of a set of TED talks (some originally given in English, some in Chinese) that have been annotated with discourse relations in the style of the Penn Discourse TreeBank, adapted to properties of Chinese text that are not present in English. The resource is currently unique in annotating discourse-level properties of planned spoken monologues rather than of written text. An inter-annotator agreement study demonstrates that the annotation scheme is able to achieve highly reliable results.

Key facts. Cited by 13 papers in the map (data through 13 Oct 2026). First posted on arXiv 9 Mar 2020.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 0; 2023: 3; 2024: 1; 2025: 8.

13 papers.

Sort:

By area:

  1. 2023Consistency is Key: Disentangling Label Variation in Natural Language Processing with Intra-Annotator Agreementcited by 23
  2. 2021Probing Multilingual Language Models for Discoursecited by 12
  3. 2025The Box is in the Pen: Evaluating Commonsense Reasoning in Neural Machine Translationcited by 5
  4. 2023Instances and Labels: Hierarchy-aware Joint Supervised Contrastive Learning for Hierarchical Multi-Label Text Classificationcited by 4
  5. 2023BUCA: A Binary Classification Approach to Unsupervised Commonsense Question Answeringcited by 3
  6. 2025Tgea: An error-annotated dataset and benchmark tasks for text generation from pretrained language modelscited by 1
  7. 2025Fine-Grained Evaluation for Implicit Discourse Relation Recognitioncited by 1
  8. 2025Evaluating Discourse Cohesion in Pre-trained Language Modelscited by 1
  9. 2024Meta-RTL: Reinforcement-Based Meta-Transfer Learning for Low-Resource Commonsense Reasoningcited by 0
  10. 2025Similarity-Based Domain Adaptation with LLMscited by 0
  11. 2025MetaXCR: Reinforcement-Based Meta-Transfer Learning for Cross-Lingual Commonsense Reasoningcited by 0
  12. 2025Joint Training And Decoding for Multilingual End-to-End Simultaneous Speech Translationcited by 0
1 more
  1. 2025AdaST: Dynamically Adapting Encoder States in the Decoder for End-to-End Speech-to-Text Translationcited by 0