| Name | tieval JSON |
| Version |
0.1.4
JSON |
| download |
| home_page | None |
| Summary | A framework for evaluation and development of temporal-aware models. |
| upload_time | 2024-12-13 21:24:53 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT License Copyright (C) 2023, INESC TEC tieval: An Evaluation Framework for Temporal Information Extraction Systems This software is authored by: Hugo Sousa You can reach INESC TEC Technology Licensing Office (TLO) at info.sal@inesctec.pt, or Campus da Faculdade de Engenharia da Universidade do Porto Rua Dr. Roberto Frias 4200-465 Porto Portugal Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
temporal information
evaluation
temporal information extraction
temporal relation classification
temporal relation extraction
temporal expression identification
event identification
event classification
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# tieval
[](https://pypi.org/project/tieval/)
[](https://tieval.readthedocs.io/en/latest/?badge=latest)
[](LICENSE)
[](https://dl.acm.org/doi/abs/10.1145/3539618.3591892)
A framework for evaluation and development of temporally aware models.
## Installation
The package is available on [PyPI](https://pypi.org/project/tieval/):
```shell
pip install tieval
```
It requires Python 3.8 or above.
## Usage
To understand its usability refer to the notebooks available [here]().
## Data
Throughout the last two decades many datasets have been developed to train this task.
tieval provides an easy interface to download the available corpus.
To know more about the module run the following code on the terminal.
```shell
python -m tieval download --help
```
## How to ...
In this section, we summarize how to perform the most useful operations in tieval.
### download a dataset.
```python
from pathlib import Path
from tieval import datasets
data_path = Path("data/")
datasets.download("TimeBank", data_path)
```
### load a dataset.
```python
from tieval import datasets
te3 = datasets.read("tempeval_3")
```
### load a model.
```python
from tieval import models
model = models.TimexIdentificationBaseline()
```
### make predictions.
```python
pred = model.predict(te3.test)
```
### evaluate predictions.
```python
from tieval import evaluate
annot = {doc.name: doc.timexs for doc in te3.test}
results = evaluate.timex_identification(annot, pred)
```
## Contributing
1. Fork it (https://github.com/LIAAD/tieval)
2. Create your feature branch (`git checkout -b feature/fooBar`)
3. Commit your changes (`git commit -am 'Add some fooBar'`)
4. Push to the branch (`git push origin feature/fooBar`)
5. Create a new Pull Request
## Meta
Hugo Sousa - hugo.o.sousa@inesctec.pt
This framework is part of the [Text2Story](https://text2story.inesctec.pt/) project which 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)
## Publications
If you use `tieval` in your work please site the following article:
```bibtex
@inproceedings{10.1145/3539618.3591892,
author = {Sousa, Hugo and Campos, Ricardo and Jorge, Al\'{\i}pio M\'{a}rio},
title = {Tieval: An Evaluation Framework for Temporal Information Extraction Systems},
year = {2023},
isbn = {9781450394086},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3539618.3591892},
doi = {10.1145/3539618.3591892},
booktitle = {Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {2871–2879},
numpages = {9},
keywords = {temporal information extraction, evaluation, python package},
location = {Taipei, Taiwan},
series = {SIGIR '23}
}
```
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"description": "# tieval\n\n[](https://pypi.org/project/tieval/)\n[](https://tieval.readthedocs.io/en/latest/?badge=latest)\n\n[](LICENSE)\n\n\n[](https://dl.acm.org/doi/abs/10.1145/3539618.3591892)\n\nA framework for evaluation and development of temporally aware models.\n\n\n\n## Installation\n\nThe package is available on [PyPI](https://pypi.org/project/tieval/):\n\n```shell\npip install tieval\n```\n\nIt requires Python 3.8 or above.\n\n## Usage\n\nTo understand its usability refer to the notebooks available [here]().\n\n## Data\n\nThroughout the last two decades many datasets have been developed to train this task.\ntieval provides an easy interface to download the available corpus.\n\nTo know more about the module run the following code on the terminal.\n\n```shell\npython -m tieval download --help\n```\n\n## How to ...\n\nIn this section, we summarize how to perform the most useful operations in tieval.\n\n### download a dataset.\n\n```python\nfrom pathlib import Path\nfrom tieval import datasets\n\ndata_path = Path(\"data/\")\ndatasets.download(\"TimeBank\", data_path)\n```\n\n### load a dataset.\n\n```python\nfrom tieval import datasets\n\nte3 = datasets.read(\"tempeval_3\")\n```\n\n### load a model.\n\n```python\nfrom tieval import models\n\nmodel = models.TimexIdentificationBaseline()\n```\n\n### make predictions.\n\n```python\npred = model.predict(te3.test)\n```\n\n### evaluate predictions.\n\n```python\nfrom tieval import evaluate\n\nannot = {doc.name: doc.timexs for doc in te3.test}\nresults = evaluate.timex_identification(annot, pred)\n```\n\n## Contributing\n\n1. Fork it (https://github.com/LIAAD/tieval)\n2. Create your feature branch (`git checkout -b feature/fooBar`)\n3. Commit your changes (`git commit -am 'Add some fooBar'`)\n4. Push to the branch (`git push origin feature/fooBar`)\n5. Create a new Pull Request\n\n## Meta\n\nHugo Sousa - hugo.o.sousa@inesctec.pt\n\nThis framework is part of the [Text2Story](https://text2story.inesctec.pt/) project which is financed by the ERDF \u2013\nEuropean Regional Development Fund through the North Portugal Regional Operational Programme (NORTE 2020), under the\nPORTUGAL 2020 and by National Funds through the Portuguese funding agency, FCT - Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia\nwithin project PTDC/CCI-COM/31857/2017 (NORTE-01-0145-FEDER-03185) \n\n## Publications\n\nIf you use `tieval` in your work please site the following article:\n\n\n```bibtex\n@inproceedings{10.1145/3539618.3591892,\n author = {Sousa, Hugo and Campos, Ricardo and Jorge, Al\\'{\\i}pio M\\'{a}rio},\n title = {Tieval: An Evaluation Framework for Temporal Information Extraction Systems},\n year = {2023},\n isbn = {9781450394086},\n publisher = {Association for Computing Machinery},\n address = {New York, NY, USA},\n url = {https://doi.org/10.1145/3539618.3591892},\n doi = {10.1145/3539618.3591892},\n booktitle = {Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval},\n pages = {2871\u20132879},\n numpages = {9},\n keywords = {temporal information extraction, evaluation, python package},\n location = {Taipei, Taiwan},\n series = {SIGIR '23}\n}\n```\n",
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