Papers by Prashant Shiralkar
TriggerNER: Learning with Entity Triggers as Explanations for Named Entity Recognition (2020.acl-main)
Copied to clipboard
| Challenge: | Named entity recognition (NER) is a fundamental information extraction task that focuses on extracting entities from a given text and classifying them using pre-defined categories. |
| Approach: | They propose to use “entity triggers” to facilitate label-efficient learning of NER models. |
| Outcome: | The proposed model is significantly more cost-effective than the traditional neural NER frameworks. |
OpenCeres: When Open Information Extraction Meets the Semi-Structured Web (N19-1)
Copied to clipboard
| Challenge: | Open Information Extraction (OpenIE) is a problem of extracting triples from natural language text whose predicate relations are not aligned to any pre-defined ontology. |
| Approach: | They propose an open-source method to extract triples from semi-structured websites . they use a semi-supervised label propagation technique to create training data for relations . |
| Outcome: | The proposed method extracts over 2 million triples from 31 websites in the movie vertical. |
ZeroShotCeres: Zero-Shot Relation Extraction from Semi-Structured Webpages (2020.acl-main)
Copied to clipboard
| Challenge: | Existing work on information extraction from semi-structured websites has relied on manual data annotation and learning a model specific to a given template. |
| Approach: | They propose a solution for “zero-shot” open-domain relation extraction from webpages with previously unseen templates using a graph neural network-based approach. |
| Outcome: | The proposed model provides a 31% gain over baseline for zero-shot extraction in a new subject vertical. |
Extracting Shopping Interest-Related Product Types from the Web (2023.findings-acl)
Copied to clipboard
| Challenge: | Existing e-commerce products are limited in their ability to assist customers in interest-oriented shopping. |
| Approach: | They propose to extract PTs from Web pages containing hand-crafted PT recommendations for SIs . they propose to use tree-transformer encoders for node classification to improve inter-node dependency modeling . |
| Outcome: | The proposed model outperforms the best baseline model by 2.37 F1 points on a WebPT dataset. |
Multi-modal Information Extraction from Text, Semi-structured, and Tabular Data on the Web (2020.acl-tutorials)
Copied to clipboard
| Challenge: | a tutorial explores the commonalities in the challenges and solutions developed to address information extraction from the World Wide Web. |
| Approach: | This tutorial examines methods for extracting information from the World Wide Web . it explores the commonalities in the challenges and solutions developed to address these different forms of text . |
| Outcome: | This paper examines the commonalities in the challenges and solutions developed to address the World Wide Web. |