Papers by Angel Daza
Translate and Label! An Encoder-Decoder Approach for Cross-lingual Semantic Role Labeling (D19-1)
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| Challenge: | Unlike annotation projection techniques, our model does not need parallel data during inference time. |
| Approach: | They propose a cross-lingual Encoder-Decoder model that simultaneously translates and generates sentences with semantic role annotations in a resource-poor target language. |
| Outcome: | The proposed model can be applied in monolingual, multilingual and cross-lingual settings and produces dependency-based and span-based annotations. |
X-SRL: A Parallel Cross-Lingual Semantic Role Labeling Dataset (2020.emnlp-main)
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| Challenge: | Existing multilingual SRL datasets contain disparate annotation styles or come from different domains, hampering generalization in multilingual learning. |
| Approach: | They propose to automatically construct an SRL corpus that is parallel in four languages with unified predicate and role annotations that are fully comparable across languages. |
| Outcome: | The proposed method improves performance for English SRL in weaker languages. |
Weisfeiler-Leman in the Bamboo: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity (2021.tacl-1)
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| Challenge: | Existing metrics for assessing the similarity of abstract meaning representations (AMRs) have complementary strengths and weaknesses, and are expensive to implement. |
| Approach: | They propose a Benchmark for AMR Metrics based on overt objectives that can be used to assess graph-based similarity metrics. |
| Outcome: | The proposed metrics match contextualized substructures and induce n:m alignments between their nodes. |
Dealing with Abbreviations in the Slovenian Biographical Lexicon (2022.emnlp-main)
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| Challenge: | Abbreviations are a significant challenge for NLP systems because they cause tokenization and out-of-vocabulary errors. |
| Approach: | They propose a method for identifying abbreviations in a Slovenian biographical lexicon . they use a newly developed dataset to evaluate the method against common ad-hoc solutions . |
| Outcome: | The proposed method performs better than ad-hoc solutions on a Slovenian biographical lexicon. |