Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
10K - 100K
License:
Update README.md
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README.md
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dataset_size: 6268493
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---
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# Dataset Card for
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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FabNER is a manufacturing text corpus of 350,000+ words for Named Entity Recognition.
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It is a collection of abstracts obtained from Web of Science through known journals available in manufacturing process
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science research.
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For every word, there were categories/entity labels defined namely Material (MATE), Manufacturing Process (MANP),
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Machine/Equipment (MACEQ), Application (APPL), Features (FEAT), Mechanical Properties (PRO), Characterization (CHAR),
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Parameters (PARA), Enabling Technology (ENAT), Concept/Principles (CONPRI), Manufacturing Standards (MANS) and
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BioMedical (BIOP). Annotation was performed in all categories along with the output tag in 'BIOES' format:
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dataset_size: 6268493
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---
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# Dataset Card for FabNER
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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FabNER is a manufacturing text corpus of 350,000+ words for Named Entity Recognition.
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It is a collection of abstracts obtained from Web of Science through known journals available in manufacturing process
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science research.
|
| 257 |
+
For every word, there were categories/entity labels defined, namely Material (MATE), Manufacturing Process (MANP),
|
| 258 |
Machine/Equipment (MACEQ), Application (APPL), Features (FEAT), Mechanical Properties (PRO), Characterization (CHAR),
|
| 259 |
Parameters (PARA), Enabling Technology (ENAT), Concept/Principles (CONPRI), Manufacturing Standards (MANS) and
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| 260 |
BioMedical (BIOP). Annotation was performed in all categories along with the output tag in 'BIOES' format:
|