Papers by Wahed Hemati
Recognizing Sentence-level Logical Document Structures with the Help of Context-free Grammars (2020.lrec-1)
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| Challenge: | Current sentence boundary detectors split documents into sequentially ordered sentences without their dependencies. |
| Approach: | They propose a tool that segments sentences into tree structures to detect recursive structure . they retrain different constituency parsers to transform them into sentence segmenters . |
| Outcome: | The proposed tool can detect recursive structure in documents with a main clause and subordinate clauses . the proposed tool improves German dependency parsing by providing additional structural information. |
When Specialization Helps: Using Pooled Contextualized Embeddings to Detect Chemical and Biomedical Entities in Spanish (D19-57)
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| Challenge: | Existing work on pharmacological entities requires manual annotation of these units. |
| Approach: | They propose an approach to task 1 of the PharmaCoNER Challenge to recognize pharmacological entities on a spanish corpus. |
| Outcome: | The proposed approach achieves 89.76% score on a spanish corpus based on pre-trained embeddings and 90.52% score on domain-specific embeddables. |
FastSense: An Efficient Word Sense Disambiguation Classifier (L18-1)
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| Challenge: | Word Sense Disambiguation (WSD) is a task that is often overlooked by NLP pipelines because of its complexity and complexity. |
| Approach: | They propose a neural network-based tool for word sense disambiguation called fastSense. |
| Outcome: | The proposed tool can process huge amounts of data quickly and surpasses state-of-the-art tools in terms of F-measure. |