Coreference resolution in NLP
Coreference resolution in natural language processing (NLP), answering the question, who? is one of the most challenging problems that all researchers encounter. In this blog, we will explore the principles and issues involved in resolving anaphoric pronouns in natural language processing. Anaphoric pronouns are a set of pronouns linked to a single noun or noun phrase. For example, in the sentence “I saw him yesterday”, it is obvious that there is only one person being referred to as ‘him’ and not two people by saying either ‘he sees me’ or ‘she sees me’. With this blog post, we hope to clear some of the grey areas that surround resolving anaphoric pronouns in natural language processing and provide you with some insights on resolving anaphoric pronouns in nlp for your further research purposes.
What is an anaphoric pronoun?
An anaphoric pronoun is a pronoun that is directly attached to the subject of the sentence, in other words ‘referential’. There are three types of anaphoric pronouns in English: possessive, wh- (who, whom, whose) and relative anaphora. Let us look into each type of anaphoric pronouns in English sentence below.
Anaphoric pronouns in natural language processing
Anaphoric pronouns in natural language processing refer back to a specific noun in a sentence. Anaphoric pronouns are important to understand because they identify a noun, a single person within a sentence. Anaphoric pronouns are usually resolved by defining the noun that is being referenced and then using the right anaphoric pronoun to refer back to the noun. In order to know how to resolve an anaphor, we first need to know what anaphora are and how we resolve them in NLP. Anaphora is a relationship between a word and a following word that has a similar grammatical function such as a noun or a pronoun. Some examples of anaphoric pronouns are ‘who’, ‘whom’, ‘whose’, ‘whosever’, ‘however’, ‘whensoever’, ‘wherever’, ‘whatever’ and ‘whichever’.
Principles to resolve anaphoric pronouns in nlp
Multiple pronouns can be confusing when trying to understand the context of a sentence. Therefore, most NLP systems rely on a set of principles to resolve anaphoric pronouns in nlp. These principles are based on factors such as the relation between the noun and pronouns in the sentence and the context of the sentence. Some of the most common principles used to resolve anaphoric pronouns in nlp are as follows. – The anaphor should be easily identifiable. If the anaphor is ambiguous, then it is likely to cause confusion while reading the sentence. – The anaphor should be situated near to the noun it refers to. If the anaphor is far away from the noun, it produces ambiguity, so the noun should be easily identifiable. – The anaphor should be of the same type as the noun it refers to. If the anaphor is of a different type, it creates confusion, so the anaphor should be of the same type as the noun it refers to. – The anaphor should be easily locatable. If the anaphor is ambiguous, then it is likely to cause confusion while reading the sentence. Therefore, it is important to locate the anaphor to get the correct meaning of the sentence. – The anaphor should be easily identifiable. If the anaphor is ambiguous, then it is likely to cause confusion while reading the sentence. Therefore, it is important to locate the anaphor to get the correct meaning of the sentence.
Semi-automatic rule based resolutions
Semi-automatic rule based resolutions are rule based resolutions that require some type of human intervention to resolve anaphor. Some of the rule based resolutions include using the pronoun in the sentence, using the pronoun in the question, using the pronoun in the answer, using the pronoun in the wh-clause, using a default pronoun or using a set of heuristics to resolve anaphoric pronouns.
Fully automatic rule based resolutions
Fully automatic rule based resolutions are rule based resolutions that require no human intervention to resolve anaphoric pronouns. Some of the rule based resolutions include using the pronoun in the sentence, using the pronoun in the question, using the pronoun in the answer, using the pronoun in the wh-clause, using a default pronoun, using the numeric distance between the pronoun and the noun and using the tokenized sentence to resolve anaphoric pronouns.
Summary
Anaphoric pronouns are a challenging problem in natural language processing. Resolving anaphoric pronouns is a complex problem that requires a lot of creativity and problem solving by the researchers. In this blog, we discussed what an anaphoric pronoun is and how it is resolved in nlp. We also discussed how anaphoric pronouns are resolved in nlp using principles and fully automatic rule based resolutions. We hope this blog post has provided you with some insights on resolving anaphor in nlp for your further research purposes.