Named entity recognition code run with 5 different sentences and the output is provided below.

Explain in brief the outputs of the code.

import spacy

nlp = spacy.load("en_core_web_sm")

doc = nlp("Samsungs new Galaxy S23 Ultra arrives with a 200-megapixel camera")

for ent in doc.ents:

print(ent.text, ent.start_char, ent.end_char, ent.label_)

Outputs with 5 diferent sentences on the same code:

1. Samsungs new Galaxy S23 Ultra arrives with a 200-megapixel camera

Output: Samsung 0 7 ORG

Galaxy S23 Ultra 14 30 PRODUCT

200 46 49 CARDINAL

2. Netflix lists rules and exemptions to prevent account sharing outside household

Output: Netflix 0 7 ORG

3. Zopa, the UK neobank, raises $93M more at a $1B+ valuation

Output: UK 10 12 GPE

$93M 29 33 MONEY

1B+ 45 48 MONEY

4. The Biden administration says Apples and Googles app stores are stifling competition

Output: Biden 4 9 PERSON

Apples 30 37 ORG

Google 42 48 ORG

5. . Large glacier near Seattle has completely disappeared, says researcher who has tracked it for years

Output: Seattle 19 26 GPE

years 94 99 DATE