Update dataset

README.md

@@ -5,6 +5,10 @@ dataset_info:
     dtype: int64
   - name: news_id
     dtype: int64
+  - name: line_id
+    dtype: int64
+  - name: url
+    dtype: string
   - name: sentence
     dtype: string
   - name: domain
@@ -120,6 +124,8 @@ The following columns are available for every sample:
 |---|---|---|
 | index | int | A unique identifier for every sentence |
 | news_id | int | A unique identifier for the source news associated with the current sentence |
+| line_id | int | The line number within the source document |
+| url | string | The source URL of the news article from which the sentence was extracted |
 | sentence | string | The processed and anonymized sentence |
 | domain | string | The domain associated with the sentence. Can be one of: `life-death`, `it-stiinta`, `cronica-de-film` |
 | label_0 | int | The label given by the first annotator. 0 - regular, 1 - satirical |
@@ -128,11 +134,53 @@ The following columns are available for every sample:
 | label | int | The aggregated label through majority voting. This should be used for training and evaluation. 0 - regular, 1 - satirical |
 
 
-### Citation
+## License
+
+The dataset is released under the [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) License. Note that the original sentences remain under the copyright of their respective authors and are permitted for academic use only.
+
+## Citation
 
 If you use this dataset in your research, please cite as follows:
 
 ```bibtex
+@inproceedings{10.1145/3746252.3761632,
+    author      = {Sm\u{a}du, R\u{a}zvan-Alexandru and
+                   Iuga, Andreea and
+                   Cercel, Dumitru-Clementin and
+                   Pop, Florin},
+    title       = {SeLeRoSa: Sentence-Level Romanian Satire Detection Dataset},
+    year        = {2025},
+    isbn        = {9798400720406},
+    publisher   = {Association for Computing Machinery},
+    address     = {New York, NY, USA},
+    url         = {https://doi.org/10.1145/3746252.3761632},
+    doi         = {10.1145/3746252.3761632},
+    abstract    = {Satire, irony, and sarcasm are techniques that are typically
+                    used humorously or critically, rather than deceptively; they can
+                    occasionally be mistaken for factual reporting, akin to fake news. These
+                    techniques can be applied at a more granular level, allowing satirical
+                    information to be incorporated into news articles. In this paper, we
+                    introduce the first sentence-level dataset for Romanian satire detection
+                    for news articles, called SeLeRoSa. The dataset comprises 13,873 manually
+                    annotated sentences spanning various domains, including social issues, IT,
+                    science, and movies. With the rise and recent progress of large language
+                    models (LLMs) in the natural language processing literature, LLMs have
+                    demonstrated enhanced capabilities to tackle various tasks in zero-shot
+                    settings. We evaluate multiple baseline models based on LLMs in both
+                    zero-shot and fine-tuning settings, as well as transformer-based models.
+                    Our findings reveal the current limitations of these models in the
+                    sentence-level satire detection task, paving the way for new research
+                    directions.},
+    booktitle   = {Proceedings of the 34th ACM International Conference on
+                    Information and Knowledge Management},
+    pages       = {6528–6533},
+    numpages    = {6},
+    keywords    = {pretrained language models, satire detection, sentence-level
+                    classification},
+    location    = {Seoul, Republic of Korea},
+    series      = {CIKM '25}
+}
+
 @software{smadu_2025_15689794,
   author       = {Smădu, Răzvan-Alexandru and
                   Iuga, Andreea and