You will be shown an excerpt from a computer science scientific research paper, followed by a question about the paper. Please answer the question. Do not include any text in your response other than the answer.

Context: In this paper, we propose a model called ERNIE (enhanced representation through knowledge integration) by using knowledge masking strategies. In addition to basic masking strategy, we use two kinds of knowledge strategies: phrase-level strategy and entity-level strategy. We take a phrase or a entity as one unit, which is usually composed of several words. All of the words in the same unit are masked during word representation training, instead of only one word or character being masked. In this way, the prior knowledge of phrases and entities are implicitly learned during the training procedure.Instead of adding the knowledge embedding directly, ERNIE implicitly learned the information about knowledge and longer semantic dependency, such as the relationship between entities, the property of a entity and the type of a event, to guide word embedding learning. This can make the model have better generalization and adaptability. Paragraph 10 : We present a novel language representation

Question: How did ERINE model incorporate knowledge into the language model?
ERNIE use multi-level masking to incorporate knowledge into language model, which includes entity-level masking and phrase-level masking.
The reason is that to learn enhanced language representation by entity-level masking and
phrase-level masking is a main purpose of ERNIE.