Papers by Shubham Mittal

3 papers
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 .
Lost in Translation, Found in Spans: Identifying Claims in Multilingual Social Media (2023.emnlp-main)

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Challenge: Claim span identification (CSI) is an important step in fact-checking pipelines . despite its importance to journalists and fact-seekers, it remains a understudied problem .
Approach: They propose to use social media claims to identify text segments that contain a check-worthy claim or assertion in a social media post.
Outcome: The proposed dataset outperforms other cross-lingual transfer methods on multiple languages.
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.

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