PIE Dataset Card for "CoMAGC"
This is a PyTorch-IE wrapper for the CoMAGC Huggingface dataset loading script.
Data Schema
The document type for this dataset is ComagcDocument which defines the following data fields:
pmid(str): unique sentence identifiersentence(str)cancer_type(str)cge(str): change in gene expressionccs(str): change in cell statept(str, optional): proposition typeige(str, optional): initial gene expression level
and the following annotation layers:
gene(annotation type:NamedSpan, target:sentence)cancer(annotation type:NamedSpan, target:sentence)expression_change_keyword1(annotation type:SpanWithNameAndType, target:sentence)expression_change_keyword2(annotation type:SpanWithNameAndType, target:sentence)
NamedSpan is a custom annotation type that extends typical Span with the following data fields:
name(str): entity string between span start and end
SpanWithNameAndType is a custom annotation type that extends typical Span with the following data fields:
name(str): entity string between span start and endtype(str): entity type classifying the expression
See here and here for the annotation type definitions.
Document Converters
The dataset provides predefined document converters for the following target document types:
pie_documents.documents.TextDocumentWithLabeledSpansAndBinaryRelations:- labeled_spans: There are always two labeled spans in each sentence.
The first one refers to the gene, while the second one refers to the cancer.
Therefore, the
labelis either"GENE"or"CANCER". - binary_relations: There is always one binary relation in each sentence.
This relation is always established between the gene as
headand the cancer astail. The specificlabelis the related gene-class. It is obtained from inference rules (cf here), that are based on the values of the columns CGE, CCS, IGE and PT. In case no gene-class can be inferred, no binary relation is added to the document. In total to 303 of the 821 examples, there is no rule is applicable (cf here).
- labeled_spans: There are always two labeled spans in each sentence.
The first one refers to the gene, while the second one refers to the cancer.
Therefore, the