The Widely Interpretable Semantic Representation (WISeR) captures both abstract and concrete concepts as well as their relations in plain text. One major focus of this project is to design a meaning representation that can be easily converted into semantic graphs for probabilistic reasoning on dialogue context. WISeR is distinguished from general Abstract Meaning Representation (AMR) as:
- It provides deeper and richer levels of abstraction.
- It is Interpretable by non-experts in computational structures.
- It covers relations across utterances (e.g., referents, external arguments).
- WISeR - main repository
- StreamSide - annotation tool for meaning representations
- Automatic Enrichment of Abstract Meaning Representations. Ji, Y.; Williamson, G.; Choi, J. D. Proceedings of the LREC Workshop on Linguistic Annotation (LAW), 2022.
- A Cognitive Approach to Annotating Causal Constructions in a Cross-Genre Corpus. Cao, A.; Williamson, G.; Choi, J. D. Proceedings of the LREC Workshop on Linguistic Annotation (LAW), 2022.
- StreamSide: A Fully-Customizable Open-Source Toolkit for Efficient Annotation of Meaning Representations. Choi, J. D. and Williamson, G. arXiv, 2109.09853, 2021.
- UMR-Writer: A Web Application for Annotating Uniform Meaning Representations. Zhao, J.; Xue, N.; Gysel, J. V.; and Choi, J. D. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP): System Demonstrations, 2021.
- Intensionalizing Abstract Meaning Representations: Non-veridicality and Scope. Williamson, G.; Elliott, P.; Ji, Y. Proceedings of the EMNLP Workshop on Linguistic Annotation Workshop (LAW) and Designing Meaning Representations (DMR), 2021.