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Output format: training-output
to build supervised models
#801
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# Conflicts: # bioresources/src/main/resources/org/clulab/reach/kb/NER-Grounding-Override.tsv.gz # bioresources/src/main/resources/org/clulab/reach/kb/ner/BioProcess.tsv.gz # bioresources/src/main/resources/org/clulab/reach/kb/ner/CellLine.tsv.gz # bioresources/src/main/resources/org/clulab/reach/kb/ner/CellType.tsv.gz # bioresources/src/main/resources/org/clulab/reach/kb/ner/Cellular_component.tsv.gz # bioresources/src/main/resources/org/clulab/reach/kb/ner/Disease.tsv.gz # bioresources/src/main/resources/org/clulab/reach/kb/ner/Family.tsv.gz # bioresources/src/main/resources/org/clulab/reach/kb/ner/Gene_or_gene_product.tsv.gz # bioresources/src/main/resources/org/clulab/reach/kb/ner/Organ.tsv.gz # bioresources/src/main/resources/org/clulab/reach/kb/ner/Simple_chemical.tsv.gz # bioresources/src/main/resources/org/clulab/reach/kb/ner/Site.tsv.gz # bioresources/src/main/resources/org/clulab/reach/kb/ner/Species.tsv.gz # bioresources/src/main/resources/org/clulab/reach/kb/ner/TissueType.tsv.gz
…statistics events. Added support for significance and confidence intervals to the arizona output (and possibly to the CMU by extension)
# Conflicts: # src/main/scala/org/clulab/reach/ReachCLI.scala
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The crossScalaVersion does need to be changed for publication.
export/src/main/scala/org/clulab/reach/export/TrainingDataExporter.scala
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export/src/main/scala/org/clulab/reach/export/TrainingDataExporter.scala
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export/src/main/scala/org/clulab/reach/export/TrainingDataExporter.scala
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@enoriega, this is being built for both Scala 2.11 and 2.12. The earlier version does not like trailing/dangling commas like the ones in TrainingDataExporter, so it doesn't compile. One can use |
That TrainingDataExporter still needs a comma removed at line 76 in order to work on Scala 2.11. |
…se its published version
# Conflicts: # main/src/main/resources/application.conf
Summary
Added a new output format suitable to train classifiers using a python pipeline. It "flattens" activations and regulations and creates a json array with the tokens, spans, label and polarity for each event.
Example