Performing Coreference Resolution on .mtx data file

I'm attempting to perform Coreference Resolution on this BBC dataset: http://mlg.ucd.ie/datasets/bbc.html

Using the Neuralcoref model seen here: https://github.com/huggingface/neuralcoref

However, having never worked with the .mtx file format, I'm stumped how I should pass the BBC data from the .mtx format to the spacy (and neuralcoref) pipeline.

I realize I have to use the mmread module to read the data, but how exactly would I pass the .mtx data to Spacy and Neuralcoref? Here's what I've done so far:

from scipy.io import mmread

# Specify the path to the .mtx file
file_path = "data/bbc.mtx"

# Read the .mtx file
matrix = mmread(file_path)

# Print the matrix
print(matrix)

Then, Neuralcoref's sample goes like this:

# Load your usual SpaCy model (one of SpaCy English models)
import spacy
nlp = spacy.load("en_core_web_sm")

# Add neural coref to SpaCy's pipe
import neuralcoref
neuralcoref.add_to_pipe(nlp)

# You're done. You can now use NeuralCoref as you usually manipulate a SpaCy document annotations.
doc = nlp("My sister has a dog. She loves him.")

doc._.has_coref
doc._.coref_clusters

I tried simply passing the matrix variable as

doc = nlp(matrix)

but didn't get what I expected. Would really appreciate some help, as I feel I'm out of my depth.

Solution

this won't work because the matrix from the .mtx file is a sparse matrix and doesnt contain the text required for coreference resolution.

you are looking for something like this i think

import spacy
import neuralcoref

# Load SpaCy model
nlp = spacy.load("en_core_web_sm")

# Add NeuralCoref to the pipeline
neuralcoref.add_to_pipe(nlp)

# Preprocess and concatenate the BBC text data
# Replace this with your actual preprocessing code to extract the relevant text
bbc_text = "My sister has a dog. She loves him."

# Process the BBC text data
doc = nlp(bbc_text)

# Perform coreference resolution
clusters = doc._.coref_clusters

# Print the coreference clusters
for cluster in clusters:
    main_mention = cluster.main
    mentions = cluster.mentions
    print(f"Main mention: {main_mention.text}")
    print(f"Mentions: {[mention.text for mention in mentions]}")
    print()