🚍 MyBusModel: A Custom NER Model for Public Transport Queries

BusRouteNER is a lightweight, rule-enhanced Named Entity Recognition (NER) model fine-tuned for identifying bus numbers and stops/locations in natural language queries related to public transportation in West Bengal, India.


✨ What does this model do?

This model is trained to extract two key entity types from user queries:

  • BUS_NUMBER: Recognizes bus numbers like 12C/1, S-12, 12B, etc.
  • LOCATION: Identifies source and destination locations such as Howrah, Barrackpore, Santragachi, etc.

It also filters out irrelevant noise words to give a clean and accurate entity list that can be used in downstream logic such as search, recommendations, or route-finding.


πŸ” Example

Input Query:

I want to go from Santragachi to Barrackpore, can I take 12C/1 or S-12?

Model Output:

Santragachi LOCATION

Barrackpore LOCATION

12C/1 BUS_NUMBER

S-12 BUS_NUMBER


🧠 How it works

  • Built using spaCy (en_core_web_sm) and extended with EntityRuler for custom NER logic.
  • Bus numbers and stop names are sourced from curated CSV datasets.
  • Custom regex patterns identify bus numbers with formats like 12C/1, S-12, etc.
  • Noise words like I, want, take, can, should are excluded from final entity extraction.

πŸ›  Results

  • Precision: 0.8078439964943033
  • Recall: 0.6660043352601156
  • F1 Score: 0.7300990099009901
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