A company has documents that are missing some words because of a database error. The company wants to build an ML model that can suggest potential words to fill in the missing text. Which type of…

The correct answer is D. BERT-based models. BERT-based models (Bidirectional Encoder Representations from Transformers) are suitable for tasks that involve understanding the context of words in a sentence and suggesting missing words. These models use bidirectional training, which considers the context from both…

Submitted by fernanda_arg· Mar 30, 2026Fundamentals of AI and ML

Question

A company has documents that are missing some words because of a database error. The company wants to build an ML model that can suggest potential words to fill in the missing text. Which type of model meets this requirement?

Options

ATopic modeling
BClustering models
CPrescriptive ML models
DBERT-based models

How the community answered

(30 responses)

A
7% (2)
B
3% (1)
C
17% (5)
D
73% (22)

Explanation

BERT-based models (Bidirectional Encoder Representations from Transformers) are suitable for tasks that involve understanding the context of words in a sentence and suggesting missing words. These models use bidirectional training, which considers the context from both directions (left and right of the missing word) to predict the appropriate word to fill in the gaps.

Topics

#BERT#masked language model#NLP#text completion

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