Datasets:

Languages:
English
License:
albertvillanova HF staff commited on
Commit
1ee23c8
1 Parent(s): 974437b

Update license, repo, summary, citation metadata

Browse files
Files changed (1) hide show
  1. README.md +43 -15
README.md CHANGED
@@ -6,7 +6,7 @@ language_creators:
6
  language:
7
  - en
8
  license:
9
- - unknown
10
  multilinguality:
11
  - monolingual
12
  size_categories:
@@ -76,14 +76,30 @@ dataset_info:
76
  ## Dataset Description
77
 
78
  - **Homepage:** [linnaeus](http://linnaeus.sourceforge.net/)
79
- - **Repository:**
80
  - **Paper:** [BMC Bioinformatics](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-85)
81
  - **Leaderboard:**
82
  - **Point of Contact:**
83
 
84
  ### Dataset Summary
85
 
86
- LINNAEUS is a general-purpose dictionary matching software, capable of processing multiple types of document formats in the biomedical domain (MEDLINE, PMC, BMC, OTMI, text, etc.). It can produce multiple types of output (XML, HTML, tab-separated-value file, or save to a database). It also contains methods for acting as a server (including load balancing across several servers), allowing clients to request matching over a network. A package with files for recognizing and identifying species names is available for LINNAEUS, showing 94% recall and 97% precision compared to LINNAEUS-species-corpus.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
87
 
88
  ### Supported Tasks and Leaderboards
89
 
@@ -170,23 +186,35 @@ An example from the dataset is:
170
 
171
  ### Licensing Information
172
 
173
- [More Information Needed]
174
 
175
  ### Citation Information
176
 
177
  ```bibtex
 
 
 
 
 
 
 
 
 
 
 
 
 
178
  @article{Gerner2010,
179
- abstract = {The task of recognizing and identifying species names in biomedical literature has recently been regarded as critical for a number of applications in text and data mining, including gene name recognition, species-specific document retrieval, and semantic enrichment of biomedical articles.},
180
- author = {Gerner, Martin and Nenadic, Goran and Bergman, Casey M},
181
- doi = {10.1186/1471-2105-11-85},
182
- issn = {1471-2105},
183
- journal = {BMC Bioinformatics},
184
- number = {1},
185
- pages = {85},
186
- title = {{LINNAEUS: A species name identification system for biomedical literature}},
187
- url = {https://doi.org/10.1186/1471-2105-11-85},
188
- volume = {11},
189
- year = {2010}
190
  }
191
  ```
192
 
 
6
  language:
7
  - en
8
  license:
9
+ - cc-by-4.0
10
  multilinguality:
11
  - monolingual
12
  size_categories:
 
76
  ## Dataset Description
77
 
78
  - **Homepage:** [linnaeus](http://linnaeus.sourceforge.net/)
79
+ - **Repository:** https://github.com/cambridgeltl/MTL-Bioinformatics-2016/tree/master/data/linnaeus-IOB
80
  - **Paper:** [BMC Bioinformatics](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-85)
81
  - **Leaderboard:**
82
  - **Point of Contact:**
83
 
84
  ### Dataset Summary
85
 
86
+ The LINNAEUS corpus consists of 100 full-text documents from the PMCOA
87
+ document set which were randomly selected. All mentions of species terms were manually
88
+ annotated and normalized to the NCBI taxonomy IDs of the intended species.
89
+
90
+ The original LINNAEUS corpus is available in a TAB-separated standoff format. The resource does not define training,
91
+ development or test subsets.
92
+
93
+ We converted the corpus into BioNLP shared task standoff format using a custom script, split it into 50-, 17-, and 33-
94
+ document training, development and test sets, and then converted these into the CoNLL format using standoff2conll.
95
+
96
+ As a full-text corpus, LINNAEUS contains comparatively frequent
97
+ non-ASCII characters, which were mapped to ASCII using the
98
+ standoff2conll -a option.
99
+ The conversion was highly accurate, but due to sentence-splitting errors within entity mentions,
100
+ the number of annotations in the converted data was larger by four (100.09%) than that
101
+ in the source data. 99.77% of names in the original annotation matched names in the converted
102
+ data.
103
 
104
  ### Supported Tasks and Leaderboards
105
 
 
186
 
187
  ### Licensing Information
188
 
189
+ This version of the dataset is licensed under [Creative Commons Attribution 4.0 International](https://github.com/cambridgeltl/MTL-Bioinformatics-2016/blob/master/LICENSE.md).
190
 
191
  ### Citation Information
192
 
193
  ```bibtex
194
+ @article{crichton2017neural,
195
+ title={A neural network multi-task learning approach to biomedical named entity recognition},
196
+ author={Crichton, Gamal and Pyysalo, Sampo and Chiu, Billy and Korhonen, Anna},
197
+ journal={BMC Bioinformatics},
198
+ volume={18},
199
+ number={1},
200
+ pages={368},
201
+ year={2017},
202
+ publisher={BioMed Central}
203
+ doi = {10.1186/s12859-017-1776-8},
204
+ issn = {1471-2105},
205
+ url = {https://doi.org/10.1186/s12859-017-1776-8},
206
+ }
207
  @article{Gerner2010,
208
+ author = {Gerner, Martin and Nenadic, Goran and Bergman, Casey M},
209
+ doi = {10.1186/1471-2105-11-85},
210
+ issn = {1471-2105},
211
+ journal = {BMC Bioinformatics},
212
+ number = {1},
213
+ pages = {85},
214
+ title = {{LINNAEUS: A species name identification system for biomedical literature}},
215
+ url = {https://doi.org/10.1186/1471-2105-11-85},
216
+ volume = {11},
217
+ year = {2010}
 
218
  }
219
  ```
220