Abstract
Background Species occurrence records are very important in the biodiversity domain. While several available corpora contain only annotations of species names or habitats and geographical locations, there is no consolidated corpus that covers all types of entities necessary for extracting species occurrence from biodiversity literature. In order to alleviate this issue, we have constructed the COPIOUS corpus—a gold standard corpus that covers a wide range of biodiversity entities. Results Two annotators manually annotated the corpus with five categories of entities, i.e. taxon names, geographical locations, habitats, temporal expressions and person names. The overall inter-annotator agreement on 200 doubly-annotated documents is approximately 81.86% F-score. Amongst the five categories, the agreement on habitat entities was the lowest, indicating that this type of entity is complex. The COPIOUS corpus consists of 668 documents downloaded from the Biodiversity Heritage Library with over 26K sentences and more than 28K entities. Named entity recognisers trained on the corpus could achieve an F-score of 74.58%. Moreover, in recognising taxon names, our model performed better than two available tools in the biodiversity domain, namely the SPECIES tagger and the Global Name Recognition and Discovery. More than 1,600 binary relations of Taxon-Habitat, Taxon-Person, Taxon-Geographical locations and Taxon-Temporal expressions were identified by applying a pattern-based relation extraction system to the gold standard. Based on the extracted relations, we can produce a knowledge repository of species occurrences. Conclusion The paper describes in detail the construction of a gold standard named entity corpus for the biodiversity domain. An investigation of the performance of named entity recognition (NER) tools trained on the gold standard revealed that the corpus is sufficiently reliable and sizeable for both training and evaluation purposes. The corpus can be further used for relation extraction to locate species occurrences in literature—a useful task for monitoring species distribution and preserving the biodiversity.
Highlights
Biodiversity plays a central role in our daily lives, given its implications on ecological resilience, food security, species and subspecies endangerment and natural sustainability
The basis for the gold standard corpus was a set of English documents downloaded from the Biodiversity Heritage Library (BHL)
We have described the process of constructing the Conserving Philippine Biodiversity by Understanding Big Data (COPIOUS) corpus, which is annotated with five entity categories relevant to the study of biodiversity: Taxon names, geographical locations, habitats, temporal expressions and persons
Summary
Biodiversity plays a central role in our daily lives, given its implications on ecological resilience, food security, species and subspecies endangerment and natural sustainability. Research in this domain has recently seen accelerated growth, leading to the "big data" scenario of the biodiversity literature. Text mining has successfully been applied to the biomedical literature (Arighi et al 2013, Wei et al 2013, Mihăilă et al 2015, Ananiadou and Thompson 2017) and more recently, it has been employed in the biodiversity domain to unlock knowledge hidden in the literature In order to alleviate this issue, we have constructed the COPIOUS corpus—a gold standard corpus that covers a wide range of biodiversity entities
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