Datasets:
Tasks:
Token Classification
Formats:
csv
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
100K - 1M
ArXiv:
License:
| license: cc-by-nc-4.0 | |
| task_categories: | |
| - token-classification | |
| language: | |
| - en | |
| pretty_name: FiNER | |
| size_categories: | |
| - 1K<n<10K | |
| multilinguality: | |
| - monolingual | |
| task_ids: | |
| - named-entity-recognition | |
| # Dataset Card for "FiNER-ORD" | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Dataset Creation and Annotation](#dataset-creation) | |
| - [Additional Information](#additional-information) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contact Information](#contact-information) | |
| ## Dataset Description | |
| - **Homepage:** [https://github.com/gtfintechlab/FiNER](https://github.com/gtfintechlab/FiNER) | |
| - **Repository:** [https://github.com/gtfintechlab/FiNER](https://github.com/gtfintechlab/FiNER) | |
| - **Paper:** [Arxiv Link]() | |
| - **Point of Contact:** [Agam A. Shah](https://shahagam4.github.io/) | |
| - **Size of train dataset file:** 1.08 MB | |
| - **Size of validation dataset file:** 135 KB | |
| - **Size of test dataset file:** 336 KB | |
| ### Dataset Summary | |
| The FiNER-Open Research Dataset (FiNER-ORD) consists of a manually annotated dataset of financial news articles (in English) | |
| collected from [webz.io](https://webz.io/free-datasets/financial-news-articles/). | |
| In total, there are 47851 news articles available in this data at the point of writing this paper. | |
| Each news article is available in the form of a JSON document with various metadata information like | |
| the source of the article, publication date, author of the article, and the title of the article. | |
| For the manual annotation of named entities in financial news, we randomly sampled 220 documents from the entire set of news articles. | |
| We observed that some articles were empty in our sample, so after filtering the empty documents, we were left with a total of 201 articles. | |
| We use <a href="https://github.com/doccano/doccano">Doccano</a>, an open-source annotation tool, | |
| to ingest the raw dataset and manually label person (PER), location (LOC), and organization (ORG) entities. | |
| For our experiments, we use the manually labeled FiNER-ORD to benchmark model performance. | |
| Thus, we make a train, validation, and test split of FiNER-ORD. | |
| To avoid biased results, manual annotation is performed by annotators who have no knowledge about the labeling functions for the weak supervision framework. | |
| The train and validation sets are annotated by two separate annotators and validated by a third annotator. | |
| The test dataset is annotated by another annotator. We present a manual annotation guide in the Appendix of the paper detailing the procedures used to create the manually annotated FiNER-ORD. | |
| After manual annotation, the news articles are split into sentences. | |
| We then tokenize each sentence, employing a script to tokenize multi-token entities into separate tokens (e.g. PER_B denotes the beginning token of a person (PER) entity | |
| and PER_I represents intermediate PER tokens). We exclude white spaces when tokenizing multi-token entities. | |
| For more details check [information in paper](https://arxiv.org/abs/2302.11157) | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Languages | |
| - It is a monolingual English dataset | |
| ## Dataset Structure | |
| ### Data Instances | |
| #### FiNER-ORD | |
| - **Size of train dataset file:** 1.08 MB | |
| - **Size of validation dataset file:** 135 KB | |
| - **Size of test dataset file:** 336 KB | |
| ### Data Fields | |
| The data fields are the same among all splits. | |
| #### conll2003 | |
| - `doc_idx`: Document ID (`int`) | |
| - `sent_idx`: Sentence ID within each document (`int`) | |
| - `gold_token`: Token (`string`) | |
| - `gold_label`: a `list` of classification labels (`int`). Full tagset with indices: | |
| ```python | |
| {'O': 0, 'PER_B': 1, 'PER_I': 2, 'LOC_B': 3, 'LOC_I': 4, 'ORG_B': 5, 'ORG_I': 6} | |
| ``` | |
| ## Dataset Creation and Annotation | |
| [Information in paper ](https://arxiv.org/abs/2302.11157) | |
| ## Additional Information | |
| This dataset is also available in the IOB format described in the [CoNLL 2003 NER shared task paper](https://aclanthology.org/W03-0419.pdf) ([tner/conll2003 format](https://github.com/asahi417/tner)). You can find this alternative dataset | |
| at: [gtfintechlab/finer-ord-bio](https://huggingface.co/datasets/gtfintechlab/finer-ord-bio). | |
| ### Licensing Information | |
| [Information in paper ](https://arxiv.org/abs/2302.11157) | |
| ### Citation Information | |
| ``` | |
| @article{shah2024finerordfinancialnamedentity, | |
| title={FiNER-ORD: Financial Named Entity Recognition Open Research Dataset}, | |
| author={Agam Shah and Abhinav Gullapalli and Ruchit Vithani and Michael Galarnyk and Sudheer Chava}, | |
| journal={arXiv preprint arXiv:2302.11157}, | |
| year={2024} | |
| } | |
| ``` | |
| ### Contact Information | |
| Please contact Agam Shah (ashah482[at]gatech[dot]edu) or Ruchit Vithani (rvithani6[at]gatech[dot]edu) about any FiNER-related issues and questions. | |
| GitHub: [@shahagam4](https://github.com/shahagam4), [@ruchit2801](https://github.com/ruchit2801) | |
| Website: [https://shahagam4.github.io/](https://shahagam4.github.io/) | |