Abstract
Dependency parsing is increasingly the popular parsing formalism in practice. This assignment provides a practice exercise in implementing the shift-reduce dependency parser of Chen and Manning (2014). This parser is a two-layer feed-forward neural network, which students implement in PyTorch, providing practice in developing deep learning models and exposure to developing parser models.- Anthology ID:
- 2021.teachingnlp-1.10
- Volume:
- Proceedings of the Fifth Workshop on Teaching NLP
- Month:
- June
- Year:
- 2021
- Address:
- Online
- Editors:
- David Jurgens, Varada Kolhatkar, Lucy Li, Margot Mieskes, Ted Pedersen
- Venue:
- TeachingNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 62–64
- Language:
- URL:
- https://aclanthology.org/2021.teachingnlp-1.10
- DOI:
- 10.18653/v1/2021.teachingnlp-1.10
- Cite (ACL):
- David Jurgens. 2021. Learning PyTorch Through A Neural Dependency Parsing Exercise. In Proceedings of the Fifth Workshop on Teaching NLP, pages 62–64, Online. Association for Computational Linguistics.
- Cite (Informal):
- Learning PyTorch Through A Neural Dependency Parsing Exercise (Jurgens, TeachingNLP 2021)
- PDF:
- https://preview.aclanthology.org/naacl-24-ws-corrections/2021.teachingnlp-1.10.pdf