mlsanityData to 7 Oct 2026

AMR Parsing is Far from Solved: GrAPES, the Granular AMR Parsing Evaluation Suite

arXiv 2312.03480 ↗First posted 6 Dec 2023cs.CLcited by 6

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Abstract (arXiv)

We present the Granular AMR Parsing Evaluation Suite (GrAPES), a challenge set for Abstract Meaning Representation (AMR) parsing with accompanying evaluation metrics. AMR parsers now obtain high scores on the standard AMR evaluation metric Smatch, close to or even above reported inter-annotator agreement. But that does not mean that AMR parsing is solved; in fact, human evaluation in previous work indicates that current parsers still quite frequently make errors on node labels or graph structure that substantially distort sentence meaning. Here, we provide an evaluation suite that tests AMR parsers on a range of phenomena of practical, technical, and linguistic interest. Our 36 categories range from seen and unseen labels, to structural generalization, to coreference. GrAPES reveals in depth the abilities and shortcomings of current AMR parsers.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 14 of its 42 references that are in the map. First posted on arXiv 6 Dec 2023.

Builds on

14 of 42 references.

References · 14

  1. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  2. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  3. 2020COGS: A Compositional Generalization Challenge Based on Semantic Interpretationcited by 260
  4. 2022Graph Pre-training for AMR Parsing and Generationcited by 55
  5. 2020AMR Parsing via Graph-Sequence Iterative Inferencecited by 47
  6. 2016An Incremental Parser for Abstract Meaning Representationcited by 34
  7. 2019Core Semantic First: A Top-down Approach for AMR Parsingcited by 24
  8. 2023SLOG: A Structural Generalization Benchmark for Semantic Parsingcited by 22
  9. 2023SMATCH++: Standardized and Extended Evaluation of Semantic Graphscited by 19
  10. 2018AMR Dependency Parsing with a Typed Semantic Algebracited by 17
  11. 2020Fast semantic parsing with well-typedness guaranteescited by 10
  12. 2021Probabilistic, Structure-Aware Algorithms for Improved Variety, Accuracy, and Coverage of AMR Alignmentscited by 9
2 more
  1. 2021Putting Words in BERT's Mouth: Navigating Contextualized Vector Spaces with Pseudowordscited by 9
  2. 2022Better Smatch = Better Parser? AMR evaluation is not so simple anymorecited by 9

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Cited by year

Citing papers per year: 2024: 3; 2025: 3.

6 papers.

  1. 2024PMB5: Gaining More Insight into Neural Semantic Parsing with Challenging Benchmarkscited by 5
  2. 2024Neural Semantic Parsing with Extremely Rich Symbolic Meaning Representationscited by 5
  3. 2024On the Role of Summary Content Units in Text Summarization Evaluationcited by 4
  4. 2025Survey of Abstract Meaning Representation: Then, Now, Futurecited by 2
  5. 2025ZOGRASCOPE: A New Benchmark for Semantic Parsing over Property Graphscited by 1
  6. 2025Evaluation of Finetuned LLMs in AMR Parsingcited by 0