NER with spaCy in NLP - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to load the English model in spaCy.

NLP

import spacy
nlp = spacy.load('[1]')

Drag options to blanks, or click blank then click option'

Aen_model

Benglish_core

Cspacy_en

Den_core_web_sm

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect model names like 'english_core' or 'en_model'.

Forgetting to install the model before loading.

The correct model name to load the small English model in spaCy is 'en_core_web_sm'.

2fill in blank

medium

Complete the code to process the text and create a spaCy Doc object.

NLP

doc = nlp('[1]')

Drag options to blanks, or click blank then click option'

Anlp

B"Apple is looking at buying a startup"

Ctext

DDoc

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the nlp object itself instead of a string.

Passing a variable name without quotes.

To create a Doc object, you pass the text string to the nlp model, e.g., nlp("Apple is looking at buying a startup").

3fill in blank

hard

Fix the error in the code to print named entities and their labels.

NLP

for ent in doc.[1]:
    print(ent.text, ent.label_)

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Aents

Blabels

Centities

Dtokens

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'tokens' or 'labels' which are not attributes of Doc for entities.

Using 'entities' which is not a valid attribute.

The correct attribute to access named entities in a Doc object is 'ents'.

4fill in blank

hard

Fill both blanks to create a dictionary of entity texts and their labels.

NLP

entities = {ent.[1]: ent.[2] for ent in doc.ents}

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Atext

Blabel_

Clabel

Dstring

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'label' without underscore which returns an integer code.

Using 'string' which is not an attribute.

Each entity has a 'text' attribute for the entity string and 'label_' attribute for the label name.

5fill in blank

hard

Fill all three blanks to filter entities with label 'ORG' and create a list of their texts.

NLP

org_entities = [ent.[1] for ent in doc.ents if ent.[2] == '[3]']

Drag options to blanks, or click blank then click option'

Atext

Blabel_

CORG

Dlabel

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'label' instead of 'label_' which gives numeric codes.

Comparing label to 'org' in lowercase which is case sensitive.

To get texts of entities labeled 'ORG', use ent.text and check ent.label_ == 'ORG'.