Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
expert-generated
License:
| annotations_creators: | |
| - expert-generated | |
| language_creators: | |
| - found | |
| language: | |
| - en | |
| license: | |
| - other | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 10K<n<100K | |
| source_datasets: [] | |
| task_categories: | |
| - token-classification | |
| task_ids: | |
| - named-entity-recognition | |
| pretty_name: FabNER is a manufacturing text dataset for Named Entity Recognition. | |
| tags: | |
| - manufacturing | |
| - 2000-2020 | |
| dataset_info: | |
| - config_name: fabner | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: tokens | |
| sequence: string | |
| - name: ner_tags | |
| sequence: | |
| class_label: | |
| names: | |
| '0': O | |
| '1': B-MATE | |
| '2': I-MATE | |
| '3': E-MATE | |
| '4': S-MATE | |
| '5': B-MANP | |
| '6': I-MANP | |
| '7': E-MANP | |
| '8': S-MANP | |
| '9': B-MACEQ | |
| '10': I-MACEQ | |
| '11': E-MACEQ | |
| '12': S-MACEQ | |
| '13': B-APPL | |
| '14': I-APPL | |
| '15': E-APPL | |
| '16': S-APPL | |
| '17': B-FEAT | |
| '18': I-FEAT | |
| '19': E-FEAT | |
| '20': S-FEAT | |
| '21': B-PRO | |
| '22': I-PRO | |
| '23': E-PRO | |
| '24': S-PRO | |
| '25': B-CHAR | |
| '26': I-CHAR | |
| '27': E-CHAR | |
| '28': S-CHAR | |
| '29': B-PARA | |
| '30': I-PARA | |
| '31': E-PARA | |
| '32': S-PARA | |
| '33': B-ENAT | |
| '34': I-ENAT | |
| '35': E-ENAT | |
| '36': S-ENAT | |
| '37': B-CONPRI | |
| '38': I-CONPRI | |
| '39': E-CONPRI | |
| '40': S-CONPRI | |
| '41': B-MANS | |
| '42': I-MANS | |
| '43': E-MANS | |
| '44': S-MANS | |
| '45': B-BIOP | |
| '46': I-BIOP | |
| '47': E-BIOP | |
| '48': S-BIOP | |
| splits: | |
| - name: train | |
| num_bytes: 4394010 | |
| num_examples: 9435 | |
| - name: validation | |
| num_bytes: 934347 | |
| num_examples: 2183 | |
| - name: test | |
| num_bytes: 940136 | |
| num_examples: 2064 | |
| download_size: 1265830 | |
| dataset_size: 6268493 | |
| - config_name: fabner_bio | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: tokens | |
| sequence: string | |
| - name: ner_tags | |
| sequence: | |
| class_label: | |
| names: | |
| '0': O | |
| '1': B-MATE | |
| '2': I-MATE | |
| '3': B-MANP | |
| '4': I-MANP | |
| '5': B-MACEQ | |
| '6': I-MACEQ | |
| '7': B-APPL | |
| '8': I-APPL | |
| '9': B-FEAT | |
| '10': I-FEAT | |
| '11': B-PRO | |
| '12': I-PRO | |
| '13': B-CHAR | |
| '14': I-CHAR | |
| '15': B-PARA | |
| '16': I-PARA | |
| '17': B-ENAT | |
| '18': I-ENAT | |
| '19': B-CONPRI | |
| '20': I-CONPRI | |
| '21': B-MANS | |
| '22': I-MANS | |
| '23': B-BIOP | |
| '24': I-BIOP | |
| splits: | |
| - name: train | |
| num_bytes: 4394010 | |
| num_examples: 9435 | |
| - name: validation | |
| num_bytes: 934347 | |
| num_examples: 2183 | |
| - name: test | |
| num_bytes: 940136 | |
| num_examples: 2064 | |
| download_size: 1258672 | |
| dataset_size: 6268493 | |
| - config_name: fabner_simple | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: tokens | |
| sequence: string | |
| - name: ner_tags | |
| sequence: | |
| class_label: | |
| names: | |
| '0': O | |
| '1': MATE | |
| '2': MANP | |
| '3': MACEQ | |
| '4': APPL | |
| '5': FEAT | |
| '6': PRO | |
| '7': CHAR | |
| '8': PARA | |
| '9': ENAT | |
| '10': CONPRI | |
| '11': MANS | |
| '12': BIOP | |
| splits: | |
| - name: train | |
| num_bytes: 4394010 | |
| num_examples: 9435 | |
| - name: validation | |
| num_bytes: 934347 | |
| num_examples: 2183 | |
| - name: test | |
| num_bytes: 940136 | |
| num_examples: 2064 | |
| download_size: 1233960 | |
| dataset_size: 6268493 | |
| - config_name: text2tech | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: tokens | |
| sequence: string | |
| - name: ner_tags | |
| sequence: | |
| class_label: | |
| names: | |
| '0': O | |
| '1': Technological System | |
| '2': Method | |
| '3': Material | |
| '4': Technical Field | |
| splits: | |
| - name: train | |
| num_bytes: 4394010 | |
| num_examples: 9435 | |
| - name: validation | |
| num_bytes: 934347 | |
| num_examples: 2183 | |
| - name: test | |
| num_bytes: 940136 | |
| num_examples: 2064 | |
| download_size: 1192966 | |
| dataset_size: 6268493 | |
| configs: | |
| - config_name: fabner | |
| data_files: | |
| - split: train | |
| path: fabner/train-* | |
| - split: validation | |
| path: fabner/validation-* | |
| - split: test | |
| path: fabner/test-* | |
| default: true | |
| - config_name: fabner_bio | |
| data_files: | |
| - split: train | |
| path: fabner_bio/train-* | |
| - split: validation | |
| path: fabner_bio/validation-* | |
| - split: test | |
| path: fabner_bio/test-* | |
| - config_name: fabner_simple | |
| data_files: | |
| - split: train | |
| path: fabner_simple/train-* | |
| - split: validation | |
| path: fabner_simple/validation-* | |
| - split: test | |
| path: fabner_simple/test-* | |
| - config_name: text2tech | |
| data_files: | |
| - split: train | |
| path: text2tech/train-* | |
| - split: validation | |
| path: text2tech/validation-* | |
| - split: test | |
| path: text2tech/test-* | |
| # Dataset Card for FabNER | |
| ## Table of Contents | |
| - [Table of Contents](#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) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [https://figshare.com/articles/dataset/Dataset_NER_Manufacturing_-_FabNER_Information_Extraction_from_Manufacturing_Process_Science_Domain_Literature_Using_Named_Entity_Recognition/14782407](https://figshare.com/articles/dataset/Dataset_NER_Manufacturing_-_FabNER_Information_Extraction_from_Manufacturing_Process_Science_Domain_Literature_Using_Named_Entity_Recognition/14782407) | |
| - **Paper:** ["FabNER": information extraction from manufacturing process science domain literature using named entity recognition](https://par.nsf.gov/servlets/purl/10290810) | |
| - **Size of downloaded dataset files:** 3.79 MB | |
| - **Size of the generated dataset:** 6.27 MB | |
| ### Dataset Summary | |
| FabNER is a manufacturing text corpus of 350,000+ words for Named Entity Recognition. | |
| It is a collection of abstracts obtained from Web of Science through known journals available in manufacturing process | |
| science research. | |
| For every word, there were categories/entity labels defined, namely Material (MATE), Manufacturing Process (MANP), | |
| Machine/Equipment (MACEQ), Application (APPL), Features (FEAT), Mechanical Properties (PRO), Characterization (CHAR), | |
| Parameters (PARA), Enabling Technology (ENAT), Concept/Principles (CONPRI), Manufacturing Standards (MANS) and | |
| BioMedical (BIOP). Annotation was performed in all categories along with the output tag in 'BIOES' format: | |
| B=Beginning, I-Intermediate, O=Outside, E=End, S=Single. | |
| For details about the dataset, please refer to the paper: ["FabNER": information extraction from manufacturing process science domain literature using named entity recognition](https://par.nsf.gov/servlets/purl/10290810) | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Languages | |
| The language in the dataset is English. | |
| ## Dataset Structure | |
| ### Data Instances | |
| - **Size of downloaded dataset files:** 3.79 MB | |
| - **Size of the generated dataset:** 6.27 MB | |
| An example of 'train' looks as follows: | |
| ```json | |
| { | |
| "id": "0", | |
| "tokens": ["Revealed", "the", "location-specific", "flow", "patterns", "and", "quantified", "the", "speeds", "of", "various", "types", "of", "flow", "."], | |
| "ner_tags": [0, 0, 0, 46, 49, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] | |
| } | |
| ``` | |
| ### Data Fields | |
| #### fabner | |
| - `id`: the instance id of this sentence, a `string` feature. | |
| - `tokens`: the list of tokens of this sentence, a `list` of `string` features. | |
| - `ner_tags`: the list of entity tags, a `list` of classification labels. | |
| ```json | |
| {"O": 0, "B-MATE": 1, "I-MATE": 2, "O-MATE": 3, "E-MATE": 4, "S-MATE": 5, "B-MANP": 6, "I-MANP": 7, "O-MANP": 8, "E-MANP": 9, "S-MANP": 10, "B-MACEQ": 11, "I-MACEQ": 12, "O-MACEQ": 13, "E-MACEQ": 14, "S-MACEQ": 15, "B-APPL": 16, "I-APPL": 17, "O-APPL": 18, "E-APPL": 19, "S-APPL": 20, "B-FEAT": 21, "I-FEAT": 22, "O-FEAT": 23, "E-FEAT": 24, "S-FEAT": 25, "B-PRO": 26, "I-PRO": 27, "O-PRO": 28, "E-PRO": 29, "S-PRO": 30, "B-CHAR": 31, "I-CHAR": 32, "O-CHAR": 33, "E-CHAR": 34, "S-CHAR": 35, "B-PARA": 36, "I-PARA": 37, "O-PARA": 38, "E-PARA": 39, "S-PARA": 40, "B-ENAT": 41, "I-ENAT": 42, "O-ENAT": 43, "E-ENAT": 44, "S-ENAT": 45, "B-CONPRI": 46, "I-CONPRI": 47, "O-CONPRI": 48, "E-CONPRI": 49, "S-CONPRI": 50, "B-MANS": 51, "I-MANS": 52, "O-MANS": 53, "E-MANS": 54, "S-MANS": 55, "B-BIOP": 56, "I-BIOP": 57, "O-BIOP": 58, "E-BIOP": 59, "S-BIOP": 60} | |
| ``` | |
| #### fabner_bio | |
| - `id`: the instance id of this sentence, a `string` feature. | |
| - `tokens`: the list of tokens of this sentence, a `list` of `string` features. | |
| - `ner_tags`: the list of entity tags, a `list` of classification labels. | |
| ```json | |
| {"O": 0, "B-MATE": 1, "I-MATE": 2, "B-MANP": 3, "I-MANP": 4, "B-MACEQ": 5, "I-MACEQ": 6, "B-APPL": 7, "I-APPL": 8, "B-FEAT": 9, "I-FEAT": 10, "B-PRO": 11, "I-PRO": 12, "B-CHAR": 13, "I-CHAR": 14, "B-PARA": 15, "I-PARA": 16, "B-ENAT": 17, "I-ENAT": 18, "B-CONPRI": 19, "I-CONPRI": 20, "B-MANS": 21, "I-MANS": 22, "B-BIOP": 23, "I-BIOP": 24} | |
| ``` | |
| #### fabner_simple | |
| - `id`: the instance id of this sentence, a `string` feature. | |
| - `tokens`: the list of tokens of this sentence, a `list` of `string` features. | |
| - `ner_tags`: the list of entity tags, a `list` of classification labels. | |
| ```json | |
| {"O": 0, "MATE": 1, "MANP": 2, "MACEQ": 3, "APPL": 4, "FEAT": 5, "PRO": 6, "CHAR": 7, "PARA": 8, "ENAT": 9, "CONPRI": 10, "MANS": 11, "BIOP": 12} | |
| ``` | |
| #### text2tech | |
| - `id`: the instance id of this sentence, a `string` feature. | |
| - `tokens`: the list of tokens of this sentence, a `list` of `string` features. | |
| - `ner_tags`: the list of entity tags, a `list` of classification labels. | |
| ```json | |
| {"O": 0, "Technological System": 1, "Method": 2, "Material": 3, "Technical Field": 4} | |
| ``` | |
| ### Data Splits | |
| | | Train | Dev | Test | | |
| |--------|-------|------|------| | |
| | fabner | 9435 | 2183 | 2064 | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| #### Who are the source language producers? | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| #### Who are the annotators? | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Personal and Sensitive Information | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Discussion of Biases | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Other Known Limitations | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Licensing Information | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Citation Information | |
| ``` | |
| @article{DBLP:journals/jim/KumarS22, | |
| author = {Aman Kumar and | |
| Binil Starly}, | |
| title = {"FabNER": information extraction from manufacturing process science | |
| domain literature using named entity recognition}, | |
| journal = {J. Intell. Manuf.}, | |
| volume = {33}, | |
| number = {8}, | |
| pages = {2393--2407}, | |
| year = {2022}, | |
| url = {https://doi.org/10.1007/s10845-021-01807-x}, | |
| doi = {10.1007/s10845-021-01807-x}, | |
| timestamp = {Sun, 13 Nov 2022 17:52:57 +0100}, | |
| biburl = {https://dblp.org/rec/journals/jim/KumarS22.bib}, | |
| bibsource = {dblp computer science bibliography, https://dblp.org} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@phucdev](https://github.com/phucdev) for adding this dataset. |