| --- |
| license: cc-by-4.0 |
| language: |
| - zh |
| pretty_name: CSRTE-Text |
| tags: |
| - text-relation-extraction |
| - relation-extraction |
| - chinese |
| --- |
| |
| # CSRTE-Text |
|
|
| CSRTE-Text is the text-only counterpart of the CSRTE Chinese relation extraction benchmark. It contains transcriptions with named-entity and relation annotations, and is intended for text-only SpeechRE experiments, analysis, and comparison with the audio-based benchmark. |
|
|
| ## Data format |
|
|
| The dataset is provided in `train.json`, `dev.json`, and `test.json`. Each JSON record contains: |
|
|
| - `sentence`: the transcription of the utterance. |
| - `audio_id`: the identifier inherited from the paired speech record. |
| - `data_annotation`: entity spans and relation annotations. Entity spans use `start`, `end`, `text`, and `labels`; relations identify their source and target entities and relation labels. |
| - `data_info`: available metadata associated with the utterance. |
|
|
| `dataset_info.json` lists the entity and relation label sets used by CSRTE. |
|
|
| ## License |
|
|
| The dataset is released under the [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/). Please check the licenses and terms of the underlying sources before redistribution or commercial use. |
|
|
| ## Citation |
|
|
| CSRTE was introduced and used by the following work: |
|
|
| ```bibtex |
| @inproceedings{mu-etal-2026-acre, |
| title = "{ACRE}: An Acoustic-Cue and Contextual-Knowledge Reasoning Enhancement Framework for Speech Relation Extraction", |
| author = "Mu, Wenxuan and |
| Ning, Jinzhong and |
| Zhao, Di and |
| Zhang, Yijia", |
| editor = "Lee, Hung-Yi and |
| Dev, Sunipa and |
| Li, Jessy and |
| Elliott, Desmond", |
| booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2026", |
| month = oct, |
| year = "2026", |
| address = "Budapest, Hungary", |
| publisher = "Association for Computational Linguistics", |
| url = "https://aclanthology.org/2026.findings-emnlp.1244/", |
| doi = "10.18653/2026.findings-emnlp.1244", |
| pages = "26343--26352", |
| ISBN = "979-8-89176-462-0" |
| } |
| ``` |
|
|
|
|
