A Flexible and Easy-to-use Semantic Role Labeling Framework for Different Languages (C18-2)
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| Challenge: | DAMESRL is an open source framework for deep semantic role labeling . language-specific characteristics and the available amount of training data influence the optimal model structure . |
| Approach: | They propose an open-source framework for deep semantic role labeling that is available under the Apache 2.0 license. |
| Outcome: | The proposed framework is available under the Apache 2.0 license. |
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| Challenge: | Recent research indicates that taking advantage of complex syntactic features leads to favorable results in Semantic Role Labeling. |
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| Challenge: | InVeRo-XL is an off-the-shelf system capable of annotating text with predicate sense and semantic role labels from 7 predicated-argument structure inventories in more than 40 languages. |
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| Challenge: | Existing work on semantic role labeling (SRL) on English has focused on syntactic integration and enhanced word representation. |
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| Challenge: | Existing approaches to Semantic Role Labeling rely on discrete labels to classify predicate senses and their arguments. |
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Semantic Role Labeling as Syntactic Dependency Parsing (2020.emnlp-main)
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| Challenge: | Using propBank-style semantic role labeling, we reduce the task to syntactic dependency parsing. |
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| Challenge: | Existing approaches to semantic role labeling rely on word alignments, translation engines or preprocessing tools. |
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| Challenge: | Multilingual and cross-lingual Semantic Role Labeling (SRL) has attracted increasing attention as multilingual text representation techniques have become more effective and widely available. |
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| Challenge: | Existing approaches to multilingual semantic dependency parsing treat languages independently, without exploiting similarities between semantic structures across languages. |
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