Abstract
We propose a semantic parsing dataset focused on instruction-driven communication with an agent in the game Minecraft. The dataset consists of 7K human utterances and their corresponding parses. Given proper world state, the parses can be interpreted and executed in game. We report the performance of baseline models, and analyze their successes and failures.- Anthology ID:
- 2020.acl-main.427
- Volume:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4693–4714
- Language:
- URL:
- https://aclanthology.org/2020.acl-main.427
- DOI:
- 10.18653/v1/2020.acl-main.427
- Cite (ACL):
- Kavya Srinet, Yacine Jernite, Jonathan Gray, and Arthur Szlam. 2020. CraftAssist Instruction Parsing: Semantic Parsing for a Voxel-World Assistant. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 4693–4714, Online. Association for Computational Linguistics.
- Cite (Informal):
- CraftAssist Instruction Parsing: Semantic Parsing for a Voxel-World Assistant (Srinet et al., ACL 2020)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2020.acl-main.427.pdf