Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
json
Size:
100K<n<1M
Tags:
Timex
Timexs
Temporal Expression
Temporal Expressions
Temporal Information
Timex Identification
License:
| annotations_creators: | |
| - machine-generated | |
| language: | |
| - en | |
| - fr | |
| - pt | |
| - de | |
| - fr | |
| - it | |
| - es | |
| language_creators: | |
| - found | |
| license: | |
| - mit | |
| multilinguality: | |
| - multilingual | |
| pretty_name: Professor HeidelTime | |
| size_categories: | |
| - 100K<n<1M | |
| source_datasets: | |
| - original | |
| tags: | |
| - Timex | |
| - Timexs | |
| - Temporal Expression | |
| - Temporal Expressions | |
| - Temporal Information | |
| - Timex Identification | |
| - Timex Classification | |
| - Timex Extraction | |
| task_categories: | |
| - token-classification | |
| task_ids: | |
| - parsing | |
| - part-of-speech | |
| - named-entity-recognition | |
| configs: | |
| - config_name: portuguese | |
| data_files: "portuguese.json" | |
| - config_name: english | |
| data_files: "english.json" | |
| - config_name: french | |
| data_files: "french.json" | |
| - config_name: italian | |
| data_files: "italian.json" | |
| - config_name: spanish | |
| data_files: "spanish.json" | |
| - config_name: german | |
| data_files: "german.json" | |
| # Professor HeidelTime | |
| [Paper](https://dl.acm.org/doi/10.1145/3583780.3615130) [GitHub](https://github.com/hmosousa/professor_heideltime) | |
| Professor HeidelTime is a project to create a multilingual corpus weakly labeled with [HeidelTime](https://github.com/HeidelTime/heideltime), a temporal tagger. | |
| ## Corpus Details | |
| The weak labeling was performed in six languages. Here are the specifics of the corpus for each language: | |
| | Dataset | Language | Documents | From | To | Tokens | Timexs | | |
| | ----------------------- | -------- | --------- | ---------- | ---------- | ---------- | -------- | | |
| | All the News 2.0 | EN | 24,642 | 2016-01-01 | 2020-04-02 | 18,755,616 | 254,803 | | |
| | Italian Crime News | IT | 9,619 | 2011-01-01 | 2021-12-31 | 3,296,898 | 58,823 | | |
| | German News Dataset | DE | 33,266 | 2003-01-01 | 2022-12-31 | 21,617,888 | 348,011 | | |
| | ElMundo News | ES | 19,095 | 2005-12-02 | 2021-10-18 | 12,515,410 | 194,043 | | |
| | French Financial News | FR | 24,293 | 2017-10-19 | 2021-03-19 | 1,673,053 | 83,431 | | |
| | Público News | PT | 27,154 | 2000-11-14 | 2002-03-20 | 5,929,377 | 111,810 | | |
| ## Contact | |
| For more information, reach out to [Hugo Sousa](https://hugosousa.net) at <hugo.o.sousa@inesctec.pt>. | |
| This framework is a part of the [Text2Story](https://text2story.inesctec.pt) project. This project is financed by the ERDF – European Regional Development Fund through the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 and by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia within project PTDC/CCI-COM/31857/2017 (NORTE-01-0145-FEDER-03185). | |
| ## Cite | |
| If you use this work, please cite the following [paper](https://dl.acm.org/doi/10.1145/3583780.3615130): | |
| ```bibtex | |
| @inproceedings{10.1145/3583780.3615130, | |
| author = {Sousa, Hugo and Campos, Ricardo and Jorge, Al\'{\i}pio}, | |
| title = {TEI2GO: A Multilingual Approach for Fast Temporal Expression Identification}, | |
| year = {2023}, | |
| isbn = {9798400701245}, | |
| publisher = {Association for Computing Machinery}, | |
| url = {https://doi.org/10.1145/3583780.3615130}, | |
| doi = {10.1145/3583780.3615130}, | |
| booktitle = {Proceedings of the 32nd ACM International Conference on Information and Knowledge Management}, | |
| pages = {5401–5406}, | |
| numpages = {6}, | |
| keywords = {temporal expression identification, multilingual corpus, weak label}, | |
| location = {Birmingham, United Kingdom}, | |
| series = {CIKM '23} | |
| } | |
| ``` | |