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    <title>DEV Community: Emine Kıskanç</title>
    <description>The latest articles on DEV Community by Emine Kıskanç (@eminekiskanc).</description>
    <link>https://dev.to/eminekiskanc</link>
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      <title>DEV Community: Emine Kıskanç</title>
      <link>https://dev.to/eminekiskanc</link>
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      <title>Building a Local Knowledge Graph RAG System for News Analysis with Neo4j and Ollama</title>
      <dc:creator>Emine Kıskanç</dc:creator>
      <pubDate>Tue, 16 Jun 2026 14:56:24 +0000</pubDate>
      <link>https://dev.to/eminekiskanc/building-a-local-knowledge-graph-rag-system-for-news-analysis-with-neo4j-and-ollama-1dj7</link>
      <guid>https://dev.to/eminekiskanc/building-a-local-knowledge-graph-rag-system-for-news-analysis-with-neo4j-and-ollama-1dj7</guid>
      <description>&lt;p&gt;I created NewsGraphRAG as a personal deep-dive to explore the boundaries of hybrid local retrieval systems. Built entirely for free and running fully locally on your machine, this project demonstrates how graph databases unlock multi-hop reasoning that traditional flat vector databases simply can't handle. By combining spaCy and Ollama (llama3.2) for a two-stage NER pipeline and using Neo4j's built-in vector index, the system extracts interconnected entities from news articles and successfully traverses relationship paths to answer complex queries with high traceability. &lt;br&gt;
Check out my latest project exploring local GraphRAG systems:&lt;/p&gt;


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      &lt;img src="https://assets.dev.to/assets/github-logo-5a155e1f9a670af7944dd5e12375bc76ed542ea80224905ecaf878b9157cdefc.svg" alt="GitHub logo"&gt;
      &lt;a href="https://github.com/emineksknc" rel="noopener noreferrer"&gt;
        emineksknc
      &lt;/a&gt; / &lt;a href="https://github.com/emineksknc/newsgraphrag" rel="noopener noreferrer"&gt;
        newsgraphrag
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&lt;div id="readme" class="MD"&gt;&lt;div class="markdown-heading"&gt;
&lt;h1 class="heading-element"&gt;Building a Local Knowledge Graph RAG System for News Analysis with Neo4j and Ollama&lt;/h1&gt;
&lt;/div&gt;
&lt;p&gt;&lt;em&gt;How graph databases unlock multi-hop reasoning that vector databases simply can't do — built entirely for free, running entirely on your machine&lt;/em&gt;&lt;/p&gt;

&lt;div class="markdown-heading"&gt;
&lt;h2 class="heading-element"&gt;The Problem with Traditional RAG&lt;/h2&gt;
&lt;/div&gt;
&lt;p&gt;Imagine you ask your news analysis system: &lt;em&gt;"What is the connection between Elon Musk and Sam Altman?"&lt;/em&gt;&lt;/p&gt;
&lt;p&gt;A traditional RAG system backed by a vector database will search for the most semantically similar chunks and likely return one article — maybe the xAI launch, or maybe the OpenAI board crisis. But the full answer spans both, and more.&lt;/p&gt;
&lt;p&gt;The complete picture is spread across multiple articles:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Article 1: Musk and Altman co-founded OpenAI, Musk departed the board in 2018&lt;/li&gt;
&lt;li&gt;Article 2: Altman was fired and reinstated as CEO during the board crisis&lt;/li&gt;
&lt;li&gt;Article 3: Musk launched xAI and later sued OpenAI, alleging it had abandoned its non-profit mission&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;The…&lt;/p&gt;&lt;/div&gt;
  &lt;/div&gt;
  &lt;div class="gh-btn-container"&gt;&lt;a class="gh-btn" href="https://github.com/emineksknc/newsgraphrag" rel="noopener noreferrer"&gt;View on GitHub&lt;/a&gt;&lt;/div&gt;
&lt;/div&gt;


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      <category>ai</category>
      <category>showdev</category>
      <category>opensource</category>
      <category>rag</category>
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