Papers by Hillel Taub-Tabib
Hierarchy Builder: Organizing Textual Spans into a Hierarchy to Facilitate Navigation (2023.acl-demo)
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| Challenge: | Information extraction systems produce hundreds to thousands of strings on a specific topic. |
| Approach: | They propose a method that allows users to consume a large collection of related textual strings in an exploratory mode. |
| Outcome: | The proposed method allows users to consume a large collection of related textual strings in an exploratory mode. |
Large Scale Substitution-based Word Sense Induction (2022.acl-long)
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| Challenge: | Word forms are ambiguous, and derive meaning from the context in which they appear . word sense induction can be performed over a corpus-derived sense inventory . |
| Approach: | They propose a word-sense induction method based on pre-trained masked language models . they train a static word embeddings algorithm on the sense-tagged corpus . |
| Outcome: | The proposed method outperforms existing senseful embeddings methods on Wikipedia and on an outlier detection dataset. |
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. |
| Approach: | They propose a query language that allows a user to search a large linguistically annotated corpus using syntactic patterns over dependency graphs. |
| Outcome: | The proposed system searches the English wikipedia and English pubmed abstracts at a rapid speed. |
A Dataset for N-ary Relation Extraction of Drug Combinations (2022.naacl-main)
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Aryeh Tiktinsky, Vijay Viswanathan, Danna Niezni, Dana Meron Azagury, Yosi Shamay, Hillel Taub-Tabib, Tom Hope, Yoav Goldberg
| Challenge: | Combination therapies are becoming standard of care for diseases such as cancer, tuberculosis, malaria and HIV. |
| Approach: | They construct an expert-annotated dataset for extracting drug combinations from the scientific literature. |
| Outcome: | The proposed dataset is the first relation extraction dataset consisting of variable-length relations. |
Neural Extractive Search (2021.acl-demo)
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| Challenge: | a domain expert often needs to extract structured information from large corpora. |
| Approach: | They propose a search paradigm called "extractive search" that extends search queries with capture-slots to allow for rapid extraction. |
| Outcome: | The proposed search paradigm can be extended with neural similarity techniques. |
Bootstrapping Relation Extractors using Syntactic Search by Examples (2021.eacl-main)
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| Challenge: | Existing methods for supervised relation extraction still require a large quantity of training data. |
| Approach: | They propose a process for bootstrapping training datasets which can be performed quickly by non-NLP-experts. |
| Outcome: | The proposed method outperforms models trained on manual and distant data augmentation techniques and the search-based approach with the NLG method. |