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Graphrag developer challenge (terni)

Terni
Bullaki
Pubblicato il 3 dicembre
Descrizione

Role DetailsGraphRAG Developer Challenge – Legal Document Processing (Prototype) Role : Senior RAG Systems Developer (Contract / Freelance) Compensation : $600 — paid only if you pass ()
95% benchmark) Timeline : 3–5 days from materials receipt to live demo Purpose : Technical evaluation for potential long-term hire Frontend / UI : None (backend prototype only) Contact : Objective We're seeking an expert in
graph-based retrieval (GraphRAG)
to build a high-accuracy prototype for legal document reasoning.
This is a paid technical test that may lead to a long-term position.
The goal is a true GraphRAG system featuring explicit knowledge-graph construction and traversal, multi-hop reasoning, agentic orchestration, and strong focus on retrieval accuracy and explainability.
Materials Provided / docs / ? Pre-processed Markdown legal documents with metadata / sample_questions.json ? Example question format / sample_answers_rag.json ? Example answer format Download materials : (Benchmark uses unseen questions.)
DeliverablesImplement two functions in Python 3.12 (Poetry project) :
def ingest(document_paths: List(str)) ->None: """Ingest Markdown docs and build the knowledge graph."""
def query(questions: List(str)) ->List(str): """Return answers with Vancouver-style citations grounded in retrieved sources."""
RequirementsNo UI, no API keys provided.
Any stack may be used.
query(...) must support parallel execution (~400 questions in =60 min) and show a progress indicator.
Test thoroughly for correctness and performance before the demo.
Live DemoIn a 60-minute live session you will : Receive ~400 unseen questions.
Run query(...) to produce /answers.json.
Explain your architecture : how the graph is built, traversed, and used to generate grounded answers.
developer(s)who wrote the code may present.
EvaluationEvaluation Passing requires an overall score above 95%, measured by (LLM as a judge) :
Faithfulness (grounded, no hallucinations)
Relevance (retrieval matches intent)
Completeness (covers key legal points)
Clarity (structured, legally coherent writing)
#J-*****-Ljbffr

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