Add CSRTE-Text dataset documentation

README.md

@@ -1,3 +1,57 @@
 ---
 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"
+}
+```
+