RepGraph: Visualising and Analysing Meaning Representation Graphs (2021.emnlp-demo)
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| Challenge: | Graph-based meaning representations provide rich semantic annotations, but visualising them clearly is more challenging than for fully lexicalized representations. |
| Approach: | They propose to use RepGraph to visualise, manipulate and analyse semantically parsed graph data in a JSON-based serialisation format. |
| Outcome: | The proposed visualisation and analysis tool supports DMRS, EDS, PTG, UCCA, and AMR semantic frameworks. |
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| Challenge: | This tutorial focuses on representing and processing sentence meaning in the form of labeled directed graphs. |
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A Survey of Meaning Representations – From Theory to Practical Utility (2024.naacl-long)
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| Challenge: | Symbolic meaning representations of natural language text have been studied since at least the 1960s . with the availability of large annotated corpora, the field has recently seen several new developments . |
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Meaning Representations for Natural Languages: Design, Models and Applications (2024.lrec-tutorials)
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| Challenge: | a tutorial reviews the design of common meaning representations and SoTA models for predicting meaning representation. |
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| Challenge: | Abstract Meaning Representation encodes acyclic graphs in PENMAN notation format . the open-source Python library Penman provides a robust parser and functions for graph inspection and manipulation . |
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| Challenge: | Empirical results suggest that the proposed methodology can be meaningfully applied to parsing into graph-structured target representations, uncovering hitherto unknown properties of the different approaches. |
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A Structured Syntax-Semantics Interface for English-AMR Alignment (N18-1)
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| Challenge: | Abstract Meaning Representation (AMR) annotations do not require explicit mapping between elements of an AMR and the corresponding elements of the sentence that evoke them. |
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A Survey of AMR Applications (2024.emnlp-main)
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| Challenge: | Abstract Meaning Representation (AMR) is a semantic representation that takes the form of a rooted, directed graph. |
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Graph Pre-training for AMR Parsing and Generation (2022.acl-long)
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| Challenge: | Abstract meaning representation (AMR) highlights the core semantic information of text in a graph structure. |
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Meaning Representations for Natural Languages: Design, Models and Applications (2022.emnlp-tutorials)
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| Challenge: | This tutorial reviews the design of common meaning representations and SoTA models for predicting meaning representation models. |
| Approach: | This tutorial reviews the design of common meaning representations and SoTA models for predicting meaning representation models. |
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