Added reference to paper

README.md

@@ -19,7 +19,7 @@ configs:
 
 *Note* that this dataset cannot be loaded using the HuggingFace datasets library as we have 2 data types within a list in the `pos` column, however you can download the dataset and load it within Python using the `json` and `gzip` core modules, an example loading script can be found at [./example_loading_script.py](./example_loading_script.py).
 
-This dataset contains the processed English Wikipedia pages of the [Mosaico](https://github.com/SapienzaNLP/mosaico/tree/main) dataset, of which this is a subset of the original English Wikipedia dataset whereby it contains only the pages with the tags `good` and `featured`.
+This dataset contains the processed English Wikipedia pages of the [Mosaico](https://github.com/SapienzaNLP/mosaico/tree/main) dataset, of which this is a subset of the original English Wikipedia dataset whereby it contains only the pages with the tags `good` and `featured`. This dataset was created as part of the following [paper](https://arxiv.org/abs/2601.09648) whereby we used this dataset to train neural based semantic taggers.
 
 Each entry in the dataset is a processed Wikipedia page containing the following annotations/tags:
 * Sentence boundaries
@@ -36,7 +36,7 @@ These annotations have been added automatically using the C version of the [CLAW
 - **Repository:** [https://github.com/UCREL/mosaico-usas-processing](https://github.com/UCREL/mosaico-usas-processing)
 - **Number of Samples** Contains 10,779 samples whereby each one represents a Wikipedia page.
 
-For more details about this dataset and how it was processed see the [GitHub repository.](https://github.com/UCREL/mosaico-usas-processing)
+For more details about this dataset and how it was processed see the [GitHub repository](https://github.com/UCREL/mosaico-usas-processing) and the associated [paper](https://arxiv.org/abs/2601.09648).
 
 ## Uses
 
@@ -650,6 +650,22 @@ The only keys that are not explained in the schema below are the following:
 }
 ```
 
+## Citation
+
+Paper: [Creating a Hybrid Rule and Neural Network Based Semantic Tagger using Silver Standard Data: the PyMUSAS framework for Multilingual Semantic Annotation](https://arxiv.org/abs/2601.09648)
+
+```
+@misc{moore2026creatinghybridruleneural,
+      title={Creating a Hybrid Rule and Neural Network Based Semantic Tagger using Silver Standard Data: the PyMUSAS framework for Multilingual Semantic Annotation}, 
+      author={Andrew Moore and Paul Rayson and Dawn Archer and Tim Czerniak and Dawn Knight and Daisy Lal and Gearóid Ó Donnchadha and Mícheál Ó Meachair and Scott Piao and Elaine Uí Dhonnchadha and Johanna Vuorinen and Yan Yabo and Xiaobin Yang},
+      year={2026},
+      eprint={2601.09648},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2601.09648}, 
+}
+```
+
 ## Dataset Card Authors
 
 * UCREL (ucrel@lancaster.ac.uk)