| Challenge: | Present-day empirical research in computational or theoretical linguistics has richly annotated and diverse corpus resources. |
| Approach: | They propose a framework for modeling arbitrary multi-modal corpus resources in a unified form for processing tools. |
| Outcome: | The proposed framework allows researchers to explore and query more diverse corpus resources and artifacts through a single interactive interface. |
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| Challenge: | Until recently, language descriptions were available in paper form only, with indexes as the only search aid. |
| Approach: | They propose to digitize a multilingual corpus of language descriptions and annotate it with various meta, word, and text attributes to make searching and analysis easier and more useful. |
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AMR Beyond the Sentence: the Multi-sentence AMR corpus (C18-1)
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Graph Matching and Graph Rewriting: GREW tools for corpus exploration, maintenance and conversion (2021.eacl-demos)
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| Challenge: | Graph Rewriting is a mathematical formalism that can be used to describe rule-based transformations on linguistic structures. |
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Corpus Considerations for Annotator Modeling and Scaling (2024.naacl-long)
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Lightweight Grammatical Annotation in the TEI: New Perspectives (L18-1)
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| Challenge: | a small set of descriptive devices have been made available for lightweight linguistic annotation . merit of a predefined TEI tagset is the homogeneity of tagging and better interoperability of simple linguistic resources encoded in the TE. |
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End-to-end Parsing of Procedural Text into Flow Graphs (2024.lrec-main)
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A Parser for LTAG and Frame Semantics (L18-1)
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How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances (2023.emnlp-main)
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Syntactic Search by Example (2020.acl-demos)
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| Challenge: | a new system allows a user to search a large linguistically annotated corpus using syntactic patterns over dependency graphs. |
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