exc_02_13.py

import spacy
from spacy.matcher import Matcher

nlp = spacy.load("en_core_web_sm")
doc = nlp(
    "Twitch Prime, the perks program for Amazon Prime members offering free "
    "loot, games and other benefits, is ditching one of its best features: "
    "ad-free viewing. According to an email sent out to Amazon Prime members "
    "today, ad-free viewing will no longer be included as a part of Twitch "
    "Prime for new members, beginning on September 14. However, members with "
    "existing annual subscriptions will be able to continue to enjoy ad-free "
    "viewing until their subscription comes up for renewal. Those with "
    "monthly subscriptions will have access to ad-free viewing until October 15."
)

# Erstelle die Patterns
pattern1 = [{"LOWER": "Amazon"}, {"IS_TITLE": True, "POS": "PROPN"}]
pattern2 = [{"LOWER": "ad-free"}, {"POS": "NOUN"}]

# Initialisiere den Matcher und füge die Patterns hinzu
matcher = Matcher(nlp.vocab)
matcher.add("PATTERN1", [pattern1])
matcher.add("PATTERN2", [pattern2])

# Iteriere über die Resultate
for match_id, start, end in matcher(doc):
    # Drucke den String-Namen des Patterns und den Text der gefundenen Span
    print(doc.vocab.strings[match_id], doc[start:end].text)