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Parallel Knowledge Graph Generation

This directory demonstrates how to parallelize knowledge graph extraction and concept generation using multiple LLM instances running on different ports. By distributing the workload across multiple LLM servers, you can significantly speed up the extraction process for large datasets.

Overview

The parallel generation approach divides your dataset into shards and processes each shard with a separate LLM instance. Each instance runs on a different port, allowing multiple extractions to happen simultaneously.

This directory includes two parallel workflows:

  1. Triple Extraction: Extract knowledge graph triples from raw text
  2. Concept Generation: Generate concepts and mappings for extracted entities

Architecture

┌─────────────────────────────────────────────────────────────┐
│                    Original Dataset                          │
└─────────────────────────────────────────────────────────────┘
                         │
                         ├─────────────────────────┐
                         │                         │
                         ▼                         ▼
              ┌─────────────────┐      ┌─────────────────┐
              │   Shard 0       │      │   Shard 1       │
              │   Port 8135     │      │   Port 8136     │
              └─────────────────┘      └─────────────────┘
                         │                         │
                         ▼                         ▼
              ┌─────────────────┐      ┌─────────────────┐
              │ LLM Instance 0  │      │ LLM Instance 1  │
              │ (localhost:8135)│      │ (localhost:8136)│
              └─────────────────┘      └─────────────────┘
                         │                         │
                         └─────────┬───────────────┘
                                   ▼
                        ┌─────────────────────┐
                        │   Merged Results    │
                        └─────────────────────┘

Prerequisites

Starting Multiple vLLM Instances

Start multiple LLM server instances on different ports. For 3 parallel instances:

# Terminal 1: Port 8135
CUDA_VISIBLE_DEVICES=0 vllm serve Qwen/Qwen2.5-7B-Instruct \
    --port 8135 --max-model-len 8192 --gpu-memory-utilization 0.9

# Terminal 2: Port 8136
CUDA_VISIBLE_DEVICES=1 vllm serve Qwen/Qwen2.5-7B-Instruct \
    --port 8136 --max-model-len 8192 --gpu-memory-utilization 0.9

# Terminal 3: Port 8137
CUDA_VISIBLE_DEVICES=2 vllm serve Qwen/Qwen2.5-7B-Instruct \
    --port 8137 --max-model-len 8192 --gpu-memory-utilization 0.9

Tips:

  • Use tmux or screen to manage multiple terminals
  • Adjust --gpu-memory-utilization based on available GPU memory
  • Use CUDA_VISIBLE_DEVICES to assign different GPUs to each instance

Files

  • 1_slice_kg_extraction.py: Triple extraction script for a single shard
  • 1_slice_kg_extraction.sh: Launches parallel triple extraction across all shards
  • 2_concept_generation.py: Concept generation script for a single shard
  • 2_concept_generation.sh: Launches parallel concept generation across all shards
  • run_full_pipeline.sh: Master script that runs both stages sequentially

Configuration

Edit the variables at the top of the shell scripts:

TOTAL_SHARDS=3        # Number of parallel processes (match number of LLM instances)
BASE_PORT=8135        # Starting port number
LOG_DIR="/path/to/log"
SCRIPT_DIR="/path/to/parallel_generation"

Port Assignment

Ports are automatically assigned: BASE_PORT + shard_number

  • Shard 0 → Port 8135
  • Shard 1 → Port 8136
  • Shard 2 → Port 8137

Usage

Quick Start (Recommended)

cd /home/httsangaj/projects/AutoSchemaKG/example/example_scripts/parallel_generation

# 1. Start LLM instances on ports 8135, 8136, 8137 (see Prerequisites)
# 2. Configure TOTAL_SHARDS and BASE_PORT in the scripts
# 3. Run the complete pipeline
./run_full_pipeline.sh

Manual Workflow

If you prefer to run each stage separately:

Stage 1: Triple Extraction

chmod +x slice_kg_extraction.sh
./slice_kg_extraction.sh

# Monitor progress
tail -f /home/httsangaj/projects/AutoSchemaKG/log/shard_*.log

Stage 2: Concept Generation

After triple extraction completes:

chmod +x concept_generation.sh
./concept_generation.sh

# Monitor progress
tail -f /home/httsangaj/projects/AutoSchemaKG/log/concept_shard_*.log