calamanCy: A Tagalog Natural Language Processing Toolkit
This toolkit addresses the development gap for Tagalog NLP by consolidating disjointed resources, though it is incremental as it builds on existing frameworks like spaCy.
The authors tackled the lack of a unified toolkit for Tagalog natural language processing by introducing calamanCy, an open-source framework built on spaCy that provides out-of-the-box support for dependency parsing, POS tagging, and NER, aiming to accelerate progress in this domain.
We introduce calamanCy, an open-source toolkit for constructing natural language processing (NLP) pipelines for Tagalog. It is built on top of spaCy, enabling easy experimentation and integration with other frameworks. calamanCy addresses the development gap by providing a consistent API for building NLP applications and offering general-purpose multitask models with out-of-the-box support for dependency parsing, parts-of-speech (POS) tagging, and named entity recognition (NER). calamanCy aims to accelerate the progress of Tagalog NLP by consolidating disjointed resources in a unified framework. The calamanCy toolkit is available on GitHub: https://github.com/ljvmiranda921/calamanCy.