# Knowledge Base Completion using Web-Based Question Answering and Multimodal Fusion

Source: [Knowledge Base Completion using Web-Based Question Answering and Multimodal Fusion](<https://www.sota2.com/research/paper/68fa6f4a1e209131cea44d1f>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T01:17:36.551Z

Authors: Yang Peng, Daisy Zhe Wang

Published: 2022-11-14T04:02:24.000Z

## Abstract

Over the past few years, large knowledge bases have been constructed to store massive amounts of knowledge. However, these knowledge bases are highly incomplete. To solve this problem, we propose a web-based question answering system system with multimodal fusion of unstructured and structured information, to fill in missing information for knowledge bases. To utilize unstructured information from the Web for knowledge base completion, we design a web-based question answering system using multimodal features and question templates to extract missing facts, which can achieve good performance with very few questions. To help improve extraction quality, the question answering system employs structured information from knowledge bases, such as entity types and entity-to-entity relatedness.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2211.07098>)

[PDF](<https://arxiv.org/pdf/2211.07098.pdf>)