task_categories:text-classification language:it license:cc-by-nc-sa-4.0 size_categories:1K<n<10K format:json modality:tabular modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
language:
- it
language_details: it-IT
license: cc-by-nc-sa-4.0
task_categories:
- text-classification
size_categories:
- 1K<n<10K
configs:
- config_name: default
  data_files:
  - split: train
    path: "data.jsonl"
  - split: trial
    path: "trial.jsonl"
  - split: test_same
    path: test-same-genre.jsonl
  - split: test_cross
    path: test-cross-genre.jsonl

---

## Dating Document Evaluation at EVALITA 2020
In the context of EVALITA 2020, we propose the task of assigning a temporal span to a document, i.e. recognising when a document was issued. The task has already been addressed in other languages, namely French, English, Polish, also in the framework of shared tasks, see for example the DÉfi Fouille de Textes (DEFT) 2010 and 2011 challenges (Grouin, 2010; Grouin, 2011), the SemEval-2015 task on Diachronic Text Evaluation (Popescu and Strapparava, 2015) and the RetroC challenge (Graliński, 2017). This task is relevant because it can play a role in document retrieval, summarisation, event detection, etc. It is also an important task per se, since it can be used to process large archival collections. In particular, when some documents in a collection have not been dated, supervised approaches could be applied to learn from the documents with a date which time span can be assigned to those who are not provided with temporal metadata. Along this line, we proposed our task taking Alcide De Gasperi’s corpus of public documents (Tonelli et al., 2019) as a use case.

In is important to note that this is a novel task for the Italian community, and therefore participating systems should be built from scratch.

The organizers rely on the honesty of all participants who might have some prior knowledge of part of the data that will be used for evaluation, not to unfairly use such knowledge.

More info on the dataset [at this link](https://dhfbk.github.io/DaDoEval/)

## Citation

If you find this useful please cite:
```
@inproceedings{menini2020dadoeval,
  title={DaDoEval@ EVALITA 2020: Same-genre and cross-genre dating of historical documents},
  author={Menini, Stefano and Moretti, Giovanni and Sprugnoli, Rachele and Tonelli, Sara and others},
  booktitle={Proceedings of the Seventh Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2020)},
  pages={391--397},
  year={2020},
  organization={Accademia University Press}
}
```