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Data · dataset · 2022

Scientific Dependency Tree Bank

Listed in Hugging Face Datasets

Annotation corpus for discourse relations benefits NLP tasks such as machine translation and question answering.

Description

SciDTB is a domain-specific discourse treebank annotated on scientific articles. Different from widely-used RST-DT and PDTB, SciDTB uses dependency trees to represent discourse structure, which is flexible and simplified to some extent but do not sacrifice structural integrity.

We discuss the labeling framework, annotation workflow and some statistics about SciDTB. Furthermore, our treebank is made as a benchmark for evaluating discourse dependency parsers, on which we provide several baselines as fundamental work.

Links

Where it is published

Catalogue records · 1

Topics

Stated by source
token classification
Inferred from text
Artificial intelligence 69%
Provenance · 1 source records, 9 field assertions
SourceKeyLast seenRaw
Hugging Face DatasetsDFKI-SLT/scidtb12 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].anzsrc:group:4602enrichment · Hugging Facetaxonomy-embedding@1.1.0title+keywords+description (69%)
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[task].hf_task:token-classificationsource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0