Felix
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1889f0b
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Parent(s):
0918c31
add seperate description for absabank-imm
Browse files- superlim-2.py +4 -1
superlim-2.py
CHANGED
@@ -32,6 +32,9 @@ Hengchen, Simon and Tahmasebi, Nina (2021). SuperSim: a test set for word simila
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_SUPERLIM_DESCRIPTION = """\
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SuperLim, A standardized suite for evaluation and analysis of Swedish natural language understanding systems.
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"""
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_DaLAJ_DESCRIPTION = """\
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Determine whether a sentence is correct Swedish or not.
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"""
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@@ -165,7 +168,7 @@ class SuperLim(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("2.0.0")
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BUILDER_CONFIGS = [
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-
datasets.BuilderConfig(name="absabank-imm", version=VERSION, description=
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datasets.BuilderConfig(name="argumentation_sent", version=VERSION, description=_argumentation_sentences_DESCRIPTION),
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datasets.BuilderConfig(name="dalaj-ged", version=VERSION, description=_DaLAJ_DESCRIPTION),
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datasets.BuilderConfig(name="sweana", version=VERSION, description=_SweAna_DESCRIPTION),
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_SUPERLIM_DESCRIPTION = """\
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SuperLim, A standardized suite for evaluation and analysis of Swedish natural language understanding systems.
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"""
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+
_ABSABank_imm_DESCRIPTION = """\
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Absabank-Imm (where ABSA stands for "Aspect-Based Sentiment Analysis" and Imm for "Immigration") is a subset of the Swedish ABSAbank, created to be a part of the SuperLim collection. In Absabank-Imm, texts and paragraphs are manually labelled according to the sentiment (on 1--5 scale) that the author expresses towards immigration in Sweden (this task is known as aspect-based sentiment analysis or stance analysis). To create Absabank-Imm, the original Absabank has been substantially reformatted, but no changes to the annotation were made. The dataset contains 4872 short texts.
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"""
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_DaLAJ_DESCRIPTION = """\
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Determine whether a sentence is correct Swedish or not.
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"""
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VERSION = datasets.Version("2.0.0")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name="absabank-imm", version=VERSION, description=_ABSABank_imm_DESCRIPTION),
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datasets.BuilderConfig(name="argumentation_sent", version=VERSION, description=_argumentation_sentences_DESCRIPTION),
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datasets.BuilderConfig(name="dalaj-ged", version=VERSION, description=_DaLAJ_DESCRIPTION),
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datasets.BuilderConfig(name="sweana", version=VERSION, description=_SweAna_DESCRIPTION),
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