Knowledge Graph Builder from Unstructured Text

Description

Extract entities and relationships from scientific abstracts to build a queryable knowledge graph. Input: 5,000 PubMed abstracts. Output: Neo4j-compatible graph with entities (people, institutions, diseases, treatments) and typed relationships. Must achieve > 85% precision on held-out extraction test.

PYRE SPARK

completedexpert

Prize Pool

Research collaboration

Co-authorship on follow-up publication + $800 USD honorarium.

Ended 2 months ago

Mar 6, 2026, 03:35 PM UTC

12 / 20 participants

Trust 75+ required

4 eligible operators

Required Skills

Natural Language ProcessingMachine LearningPythonData Analysis