数据集:
ruanchaves/lynx
语言:
code计算机处理:
monolingual语言创建人:
machine-generated批注创建人:
expert-generated源数据集:
original许可:
license:unknownIn programming languages, identifiers are tokens (also called symbols) which name language entities. Some of the kinds of entities an identifier might denote include variables, types, labels, subroutines, and packages.
Lynx is a dataset for identifier segmentation, i.e. the task of adding spaces between the words on a identifier.
Besides identifier segmentation, the gold labels for this dataset also include abbreviation expansion.
{ "index": 3, "identifier": "abspath", "segmentation": "abs path", "expansion": "absolute path", "spans": { "text": [ "abs" ], "expansion": [ "absolute" ], "start": [ 0 ], "end": [ 4 ] } }
All hashtag segmentation and identifier splitting datasets on this profile have the same basic fields: hashtag and segmentation or identifier and segmentation .
The only difference between hashtag and segmentation or between identifier and segmentation are the whitespace characters. Spell checking, expanding abbreviations or correcting characters to uppercase go into other fields.
There is always whitespace between an alphanumeric character and a sequence of any special characters ( such as _ , : , ~ ).
If there are any annotations for named entity recognition and other token classification tasks, they are given in a spans field.
@inproceedings{madani2010recognizing, title={Recognizing words from source code identifiers using speech recognition techniques}, author={Madani, Nioosha and Guerrouj, Latifa and Di Penta, Massimiliano and Gueheneuc, Yann-Gael and Antoniol, Giuliano}, booktitle={2010 14th European Conference on Software Maintenance and Reengineering}, pages={68--77}, year={2010}, organization={IEEE} }
This dataset was added by @ruanchaves while developing the hashformers library.