# Searching News Articles Using an Event Knowledge Graph Leveraged by Wikidata

arXiv: https://arxiv.org/abs/1904.05557 · HTML: https://mlsanity.com/paper/1904.05557/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Apr 2019.

## Built on by (most cited first, 13 of 13)

- [What is Event Knowledge Graph: A Survey](https://mlsanity.com/paper/2112.15280/) (2021)
- [Start from Zero: Triple Set Prediction for Automatic Knowledge Graph Completion](https://mlsanity.com/paper/2406.18166/) (2024)
- [EvEval: A Comprehensive Evaluation of Event Semantics for Large Language Models](https://mlsanity.com/paper/2305.15268/) (2023)
- [Event Causality Extraction with Event Argument Correlations](https://mlsanity.com/paper/2301.11621/) (2023)
- [Zero-Shot Cross-Lingual Document-Level Event Causality Identification with Heterogeneous Graph Contrastive Transfer Learning](https://mlsanity.com/paper/2403.02893/) (2024)
- [It's the Same Old Story! Enriching Event-Centric Knowledge Graphs by Narrative Aspects](https://mlsanity.com/paper/2205.03876/) (2022)
- [KSG: Knowledge and Skill Graph](https://mlsanity.com/paper/2209.05698/) (2022)
- [Lost in Recursion: Mining Rich Event Semantics in Knowledge Graphs](https://mlsanity.com/paper/2404.16405/) (2024)
- [BEKG: A Built Environment Knowledge Graph](https://mlsanity.com/paper/2211.02864/) (2022)
- [Explaining ELH Concept Descriptions through Counterfactual Reasoning](https://mlsanity.com/paper/2301.05109/) (2023)
- [LaSER: Language-Specific Event Recommendation](https://mlsanity.com/paper/2303.04712/) (2023)
- [Comprehensive Event Representations using Event Knowledge Graphs and Natural Language Processing](https://mlsanity.com/paper/2303.04794/) (2023)
- [A Conceptual Model for Attributions in Event-Centric Knowledge Graphs](https://mlsanity.com/paper/2503.03563/) (2025)

## Abstract (arXiv)

News agencies produce thousands of multimedia stories describing events happening in the world that are either scheduled such as sports competitions, political summits and elections, or breaking events such as military conflicts, terrorist attacks, natural disasters, etc. When writing up those stories, journalists refer to contextual background and to compare with past similar events. However, searching for precise facts described in stories is hard. In this paper, we propose a general method that leverages the Wikidata knowledge base to produce semantic annotations of news articles. Next, we describe a semantic search engine that supports both keyword based search in news articles and structured data search providing filters for properties belonging to specific event schemas that are automatically inferred.