Papers by Keshav Kolluru
mOKB6: A Multilingual Open Knowledge Base Completion Benchmark (2023.acl-short)
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| Challenge: | Open knowledge bases (Open KBCs) are constructed from triples of the form, which can be denoted as (s, r, o) by using open information extraction (Open IE) systems. |
| Approach: | They construct a dataset with facts from Wikipedia in six languages . they use open information extraction systems to extract triples from text . |
| Outcome: | The proposed dataset contains facts from Wikipedia in six languages including English . it improves existing Open KB construction pipeline by doing multilingual coreference resolution and keeping only entity-linked triples . |
Why and when should you pool? Analyzing Pooling in Recurrent Architectures (2020.findings-emnlp)
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| Challenge: | Various pooling techniques have been shown to improve performance of RNNs on text classification tasks. |
| Approach: | They propose a pooling-based variant that captures interactions among predictive tokens in a sentence. |
| Outcome: | The proposed pooling architecture outperforms non-pooling models on sequence classification tasks. |
“Covid vaccine is against Covid but Oxford vaccine is made at Oxford!” Semantic Interpretation of Proper Noun Compounds (2022.emnlp-main)
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| Challenge: | Proper noun compounds are used in short-form domains but are largely ignored in information-seeking applications. |
| Approach: | They propose to annotate a manually annotated dataset of 22.5K proper noun compounds . they use supervised learning to generate interpretations from the compounds based on target knowledge . |
| Outcome: | The proposed dataset is 60 times larger than prior noun compound datasets and includes non-compositional examples. |
Alignment-Augmented Consistent Translation for Multilingual Open Information Extraction (2022.acl-long)
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| Challenge: | Existing training data in English is limited to supervised Open Information Extraction (OpenIE) . |
| Approach: | They propose a model that automatically converts English sentences into other languages by using Alignment-Augmented Constrained Translation (AACTrans) they train a generative OpenIE model that outputs for each sentence relations in the first stage and all extractions containing the relation in the second stage. |
| Outcome: | The proposed model outperforms existing models on Spanish, Portuguese, Chinese, Hindi and Telugu on 5 languages. |
OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction (2020.emnlp-main)
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| Challenge: | OpenIE generates extractions iteratively, requiring repeated encoding of partial outputs. |
| Approach: | They propose an iterative open information extraction system that generates extractions iterativly, requiring repeated encoding of partial outputs. |
| Outcome: | The proposed system beats the previous systems by as much as 4 pts in F1 while being much faster. |
IMoJIE: Iterative Memory-Based Joint Open Information Extraction (2020.acl-main)
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| Challenge: | Recent neural OpenIE systems are statistical or rule-based for Open Information Extraction. |
| Approach: | They propose an extension to CopyAttention that produces the next extraction conditioned on all previously extracted tuples. |
| Outcome: | The proposed model outperforms CopyAttention by 18 pts and a BERT-based strong baseline by 2 ptes. |