Detect location from given text using NLP

It is possible to infer the location (country) from a given text using natural language processing (NLP) techniques. One approach is to use named entity recognition (NER) to identify location names in the text, and then use a geocoding service to map those locations to countries.

Here’s an example code in Python that uses the SpaCy library for NLP and the GeoPy library for geocoding:

!pip install spacy geopy

import spacy
from geopy.geocoders import Nominatim

# Load the SpaCy NLP model
nlp = spacy.load('en_core_web_sm')

# Initialize the GeoPy geocoder
geolocator = Nominatim(user_agent='my_app')

# Define a function to extract location names from a text using SpaCy NER
def extract_locations(text):
    doc = nlp(text)
    return [ent.text for ent in doc.ents if ent.label_ == 'LOC']

# Define a function to map location names to countries using GeoPy geocoding
def map_locations_to_countries(locations):
    countries = set()
    for location in locations:
            location = geolocator.geocode(location, addressdetails=True, exactly_one=True)
            country = location.raw['address']['country']
    return countries

# Example text to infer country from
text = "I am traveling to Paris next month."

# Extract location names from the text
locations = extract_locations(text)

# Map location names to countries
countries = map_locations_to_countries(locations)

# Print the inferred countries

In this example, we first load the SpaCy NLP model and initialize the GeoPy geocoder. We then define a function extract_locations to extract location names from a text using SpaCy NER, and a function map_locations_to_countries to map those locations to countries using GeoPy geocoding. Finally, we apply these functions to an example text “I am traveling to Paris next month” and print the inferred countries, which in this case should be France.

Note that this approach is not perfect and may not work for all texts, especially if they do not contain explicit location names or if the location names are ambiguous. Additionally, the geocoding service may have limitations or inaccuracies in mapping locations to countries. Therefore, it’s important to use this approach as part of a broader analysis and to validate the results with other sources of information.

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.