Limits...
BioCreative V track 4: a shared task for the extraction of causal network information using the Biological Expression Language.

Rinaldi F, Ellendorff TR, Madan S, Clematide S, van der Lek A, Mevissen T, Fluck J - Database (Oxford) (2016)

Bottom Line: Given the complexity of the task, we designed an evaluation methodology which gives credit to partially correct statements.We identified various levels of information expressed by BEL statements, such as entities, functions, relations, and introduced an evaluation framework which rewards systems capable of delivering useful BEL fragments at each of these levels.The aim of this evaluation method is to help identify the characteristics of the systems which, if combined, would be most useful for achieving the overall goal of automatically constructing causal biological networks from text.

View Article: PubMed Central - PubMed

Affiliation: Institute of Computational Linguistics, University of Zurich, Zurich, Switzerland fabio.rinaldi@uzh.ch juliane.fluck@scai.fraunhofer.de.

No MeSH data available.


A screenshot of the evaluation user interface of task 1.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4940434&req=5

baw067-F4: A screenshot of the evaluation user interface of task 1.

Mentions: The users can evaluate the predictions of their system using the task 1 evaluation web interface. Figure 4 shows a screenshot of the user interface. To start the evaluation, a user has to provide the input BEL statements to be evaluated as well as the submission type and an e-mail address. The submission type decides on which structural level (term, function and relationship as described below) the input will be evaluated. A user can choose between two different ways for providing input. Either a file with predictions can be uploaded to the service or predictions can be submitted directly by using the text field.Figure 4


BioCreative V track 4: a shared task for the extraction of causal network information using the Biological Expression Language.

Rinaldi F, Ellendorff TR, Madan S, Clematide S, van der Lek A, Mevissen T, Fluck J - Database (Oxford) (2016)

A screenshot of the evaluation user interface of task 1.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4940434&req=5

baw067-F4: A screenshot of the evaluation user interface of task 1.
Mentions: The users can evaluate the predictions of their system using the task 1 evaluation web interface. Figure 4 shows a screenshot of the user interface. To start the evaluation, a user has to provide the input BEL statements to be evaluated as well as the submission type and an e-mail address. The submission type decides on which structural level (term, function and relationship as described below) the input will be evaluated. A user can choose between two different ways for providing input. Either a file with predictions can be uploaded to the service or predictions can be submitted directly by using the text field.Figure 4

Bottom Line: Given the complexity of the task, we designed an evaluation methodology which gives credit to partially correct statements.We identified various levels of information expressed by BEL statements, such as entities, functions, relations, and introduced an evaluation framework which rewards systems capable of delivering useful BEL fragments at each of these levels.The aim of this evaluation method is to help identify the characteristics of the systems which, if combined, would be most useful for achieving the overall goal of automatically constructing causal biological networks from text.

View Article: PubMed Central - PubMed

Affiliation: Institute of Computational Linguistics, University of Zurich, Zurich, Switzerland fabio.rinaldi@uzh.ch juliane.fluck@scai.fraunhofer.de.

No MeSH data available.