metadata
license: cc
task_categories:
- text-generation
- text2text-generation
language:
- en
tags:
- keyphrase-generation
- paleontology
- astrophysics
- natural-language-processing
size_categories:
- 1K<n<10K
configs:
- config_name: paleo
data_files:
- split: train
path:
- paleo/train.jsonl
- split: test
path: paleo/test.jsonl
- config_name: nlp
data_files:
- split: train
path:
- nlp/train.jsonl
- split: test
path: nlp/test.jsonl
- config_name: astro
data_files:
- split: train
path:
- astro/train.jsonl
- split: test
path: astro/test.jsonl
This dataset contains the data files generated by silk, a method that leverages citation contexts to create synthetic samples of documents paired with silver-standard keyphrases for adapting keyphrase generation models to new domains. We applied silk on three domains --namely, Natural Language Processing (nlp), Astrophysics (astro)and Paleontology (paleo)--, thereby creating new adaptation data for each domain. This dataset also includes three human-labeled test sets to assess the performance of keyphrase generation across these domains.