Delete spacy_pipeline.py which was used as a demonstration

import spacy

from STSB_Dataset import STSB_Dataset

"""

Read more here:

https://spacy.io/usage/linguistic-features

"""

def print_nlp(text, mode = "pos"):

    if mode == "pos":

        nlp_list = [token.pos_ for token in text]

    if mode == "lemma":

        nlp_list = [token.lemma_ for token in text]

    if mode == "tag":

        nlp_list = [token.tag_ for token in text]

    if mode == "dep":        

        nlp_list = [token.dep_ for token in text]

    print(" ".join(nlp_list))

nlp = spacy.load("en_core_web_sm")

dataset = STSB_Dataset('data/stsbenchmark/sts-test.csv')

# spacy representation

sentences1 = []

sentences2 = []

for sentence in [s['sentence1'] for s in dataset._examples]:

    sentences1.append(nlp(sentence))

for sentence in [s['sentence2'] for s in dataset._examples]:

    sentences2.append(nlp(sentence))

doc = sentences1[1]

print("Part of speech:")

print_nlp(doc)

print("\nLemmas:")

print_nlp(doc, "lemma")

print("\nTags (related to part of speech):")

print_nlp(doc, "tag")

print("\nDependency role:")

print_nlp(doc, "dep")

print("\nDependency head/children:")

for token in doc:

    print(f"Token: {token.text}, Head: {token.head.text}, Children: {[child for child in token.children]}")