Papers by Gijs Wijnholds
Assessing Monotonicity Reasoning in Dutch through Natural Language Inference (2023.findings-eacl)
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| Challenge: | a novel dataset for natural language inference (NLI) is used to study monotonicity reasoning in Dutch. |
| Approach: | They investigate monotonicity reasoning in Dutch using a novel dataset . they find that models struggle with downward entailing contexts . |
| Outcome: | The proposed dataset shows that models struggle with downward entailing contexts, and argue that this is due to a poor understanding of negation. |
Tree Transformer’s Disambiguation Ability of Prepositional Phrase Attachment and Garden Path Effects (2024.acl-long)
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| Challenge: | Prepositional phrase attachment ambiguity is structural in nature, while garden path constructions are incremental in nature. |
| Approach: | They pretrain and evaluate an unsupervised Transformer model that induces tree representations internally and compare it to a pretrained supervised BiLSTM model. |
| Outcome: | The Tree Transformer model induces tree representations internally, but its parsing ability is inferior to the supervised BiLSTM model, and it is not as sensitive to lexical cues as other large LSTM models. |
Evaluating Composition Models for Verb Phrase Elliptical Sentence Embeddings (N19-1)
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| Challenge: | ellipsis is a natural language phenomenon where part of a sentence is missing and its information must be recovered from its context. |
| Approach: | They develop models for embedding VP-elliptical sentences using word embeddments . they extend existing verb disambiguation and sentence similarity datasets to elliptic phrases . |
| Outcome: | The proposed models outperform existing models on verb disambiguation and sentence similarity datasets and their linear counterparts. |
SICK-NL: A Dataset for Dutch Natural Language Inference (2021.eacl-main)
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| Challenge: | Having a parallel dataset for Natural Language Inference in Dutch is problematic for some NLP systems. |
| Approach: | They propose to translate a SICK dataset from English into Dutch to compare models for both languages. |
| Outcome: | The proposed dataset compares models on English and Dutch on two tasks. |
Discontinuous Constituency and BERT: A Case Study of Dutch (2022.findings-acl)
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| Challenge: | a recent study has shown that large-scale language models fail to acquire aspects of linguistic theory due to their unanticipated performance. |
| Approach: | They propose to use a context-sensitive formalism to derive grammars that capture verb nesting and verb raising in Dutch. |
| Outcome: | The proposed model fails to acquire the dependencies examined in Dutch. |