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README.md
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@@ -24,7 +24,8 @@ The training code can be found on [Github](https://github.com/oeg-upm/software_m
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The corpus have been built using two corpora in software mentions.
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* SoMESCi [1]. We have used the corpus uploaded to [Github](https://github.com/dave-s477/SoMeSci/tree/9f17a43f342be026f97f03749457d4abb1b01dbf/PLoS_sentences), more specifically, the corpus created with sentences.
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* Softcite [2]. This project has published another corpus for software mentions, which is also available on [Github](https://github.com/howisonlab/softcite-dataset/tree/master/data/corpus). We have used the annotations from bio and economics domain.
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* Papers with code. We have downloaded a list of publications from the [Papers with Code](https://paperswithcode.com/) site. You can find there publications and software from machine learning domain. To build this corpus, we have selected texts where you can find mentions of the software related with the publication.
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To build this corpus, we have removed the annotations of other entities such as version, url and those which are related with the relation of teh entity with the text. IN this case, we only use the label Application_Mention.
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The corpus have been built using two corpora in software mentions.
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* SoMESCi [1]. We have used the corpus uploaded to [Github](https://github.com/dave-s477/SoMeSci/tree/9f17a43f342be026f97f03749457d4abb1b01dbf/PLoS_sentences), more specifically, the corpus created with sentences.
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* Softcite [2]. This project has published another corpus for software mentions, which is also available on [Github](https://github.com/howisonlab/softcite-dataset/tree/master/data/corpus). We have used the annotations from bio and economics domain.
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* Papers with code. We have downloaded a list of publications from the [Papers with Code](https://paperswithcode.com/) site. You can find there publications and software from machine learning domain. To build this corpus, we have selected texts where you can find mentions of the software related with the publication. DOI: 10.5281/zenodo.10033751
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To build this corpus, we have removed the annotations of other entities such as version, url and those which are related with the relation of teh entity with the text. IN this case, we only use the label Application_Mention.
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