Word sense disambiguation (WSD) plays a crucial role in improving machine reading comprehension (MRC) systems. MRC aims to teach computers how to understand and comprehend human language text and answer questions based on it. However, the understanding of text relies heavily on the correct interpretation of individual words, which often have multiple senses or meanings.

  WSD helps in MRC by resolving the ambiguity of words within the context of the given text. It is essential because different word senses can significantly alter the meaning of a sentence or a passage. By correctly disambiguating the senses of words, MRC systems can accurately comprehend the text and provide more accurate answers.

  Here are some ways in which WSD assists in MRC:

  1. Improving question understanding: In MRC, questions are posed based on a given text. However, the questions can contain words that have multiple meanings. By disambiguating these words, the MRC system can accurately understand the question and identify the relevant information in the text to provide the correct answer.

  2. Enhancing passage comprehension: WSD helps in understanding the context of the passage by correctly identifying the sense of ambiguous words. This allows the MRC system to grasp the intended meaning of the text and answer questions based on the appropriate interpretation.

  3. Facilitating answer extraction: By disambiguating the senses of words in the passage, the MRC system can determine which words are relevant for answering a particular question. This improves the accuracy of answer extraction by selecting the right information.

  4. Resolving coreference resolution: Coreference resolution is the task of determining which pronouns or noun phrases refer to the same entity. WSD can help in resolving coreference ambiguities by correctly identifying the sense of the words involved. This ensures that the MRC system can correctly interpret and answer questions related to entities mentioned in the text.

  Overall, WSD plays a vital role in assisting MRC systems by resolving word ambiguity, improving text comprehension, and enabling accurate answer generation. By disambiguating word senses, MRC systems can better understand and answer questions based on the information presented in the given text.