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Ambiguity in language
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Ambiguities in Natural Language Processing
Anjali M K1
, Babu Anto P2
Department of Information Technology, Kannur University, Kerala, India1,2
ABSTRACT: Ambiguity can be referred as the ability of having more than one meaning or being understood in more than one way. Natural languages are ambiguous, so computers are not able to understand language the way people do.
Natural Language Processing (NLP) is concerned with the development of computational models of aspects of human language processing. Ambiguity can occur at various levels of NLP. Ambiguity could be Lexical, Syntactic, Semantic,
Pragmatic etc. This paper presents a study about different types of ambiguities that comes under Natural Language
Processing.
KEYWORDS: Ambiguity, Natural
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Consider the example,
The horse ran up the hill. It was very steep. It soon got tired.
The anaphoric reference of ‘it’ in the two situations cause ambiguity.
Steep applies to surface hence ‘it’ can be hill. Tired applies to animate object hence ‘it’ can be horse.
2.5 Pragmatic Ambiguity: Pragmatic ambiguity refers to a situation where the context of a phrase gives it multiple interpretation [2]. One of the hardest tasks in NLP.The problem involves processing user intention, sentiment, belief world, modals etc.- all of whichare highly complex tasks.[3]
Consider the example,
Tourist (checking out of the hotel): Waiter, go upstairs to myroom and see if my sandals are there; do not be late; I have tocatch the train in 15 minutes.
Waiter (running upstairs and coming back panting): Yes sir,they are there.
Clearly, the waiter is falling short of the expectation of thetourist, since he does not understand the pragmatics of the situation.[3] Pragmatic ambiguity arises when the statement is not specific, and the context does not provide the information needed to clarify the statement. Information is missing, and must be inferred.[5]
Consider the example
I love you
If you have ever had a conversation with someone whose first language is not the same as your own, you are probably familiar with the idea that there are certain words and phrases that do not translate perfectly from one language to another. This conflict is usually a matter of one language having a single word or succinct phrase for a concept which another language might need an entire sentence to capture.
364) - This leads to the confusion of a statement's meaning. Due to a phrase being unclear, it can be interpreted with many different meanings.
At times, we sometimes say things without having a full understanding of what we are talking about.
Chapter seven begins by explaining an example that would make the case against using ambiguity. In fact, the title of chapter seven is “Avoid Ambiguity”. While it is true that vague statements leave questions unanswered, the traditional idea behind gathering information is to find specific details and clear communicated information. Ambiguous communication can be dangerous in some situations where the consequences of not understanding the complete picture can cause harm. Therefore, communication of specific information is needed in some situations, however, the author then goes on to explain how the ambiguous statement or event can lead to more accurate and applicable solutions.
e-b) What context clue(s) did you expect the other person to consider so that they could accurately interpret what you said and did? (10)
Donnellen (1966) criticized the Russell and Strawson’s view. He claimed that there are attributive and referential uses of definite description. The former is about attributively using definite description in an assertion which stating something about “A is B”. The latter is about speaker using the description to let the audience to know what is “A is B” about. Donnellen claimed that Russell focus on former and Strawson focus on latter.
Pragmatics Aspects: Deixis and Distance, reference and inference, conversational implicature, anaphoric and cataphoric reference, presupposition, entailment, direct and indirect speech acts and speech events, cultural context and cross cultural pragmatics, conversational analysis and background knowledge, denotation and connotation meaning, the four maxims and hedges.
5. Independence from at-issue meaning: Conventional implicatures are logically and compositionally independent of at-issue meaning.
There are many types of polysemy, some of which view the polysemous word as having primary meaning and secondary meaning, i.e. the meaning which a word refers to in the external world and what it refers to in the second understanding of the word. Other types of polysemy can be dealt with lexically, i.e. these types view the literal meaning and the figurative meaning of the polysemous word. Accordingly, there is referential polysemy, and lexical polysemy which is subdivided into linear polysemy and subsuming polysemy.
Sentiment analysis known also as polarity classification , subjectively analysis, opinion mining, affect analysis, its relishing field of study that that deal with people’s opinions, sentiment , emotions and attitudes about different entities such as products ,service ,individuals ,companies ,events and topics; and includes many fields like natural language process, machine learning, computational linguistic ,statistics, and artificial intelligence . it’s a set of computational and natural language techniques which could be leveraged in order to extract subject information in a given text .
... applied on different Domain data sets and sub level data sets. The data sets are applied on Maximum entropy, Support Vector Machine Method, Multinomial naïve bayes algorithms, I got 60-70% of accuracy. The above is also applied for the Unigrams of Maximum entropy, Support Vector Machine Method, Multinomial naïve bayes algorithms achieved an accuracy of 65-75%. Applied the same data on proposed lexicon Based Semantic Orientation Analysis Algorithm, we received better accuracy of 85%. In subjective Feature Relation Networks Chi-square model using n-grams, POS tagging by applying linguistic rules performed with highest accuracy of 80% to 93% significantly better than traditional naïve bayes with unigram model. The after applying proposed model on different sets the results are validated with test data and proved our methods are more accurate than the other methods.
The field of Computational Linguistics is relatively new; however, it contains several sub-areas reflecting practical applications in the field. Machine (or Automatic) Translation (MT) is one of the main components of Computational Linguistics (CL). It can be considered as an independent subject because people who work in this domain are not necessarily experts in the other domains of CL. However, what connects them is the fact that all of these subjects use computers as a tool to deal with human language. Therefore, some people call it Natural Language Processing (NLP). This paper tries to highlight MT as an essential sub-area of CL. The types and approaches of MT will be considered, and limitations discussed.
Language is a means of human communication whether verbally or nonverbally. In everyday life we use language to express our thoughts, feelings ,attitudes,etc.A great amount of social interactions takes place every day over the telephone ,by online chats, face –to face interaction or at workplaces .We use language of different forms for different functions as in to inform, question , and sometimes to strengthen social relationships or just to keep the social wheels turning smoothly. Moreover, understanding one's own language and even other cultures’ language is important to arrive at a successful and effective communication with others . The study of language can be undertaken in various ways .Semantics and pragmatics are two branches of linguistics which are concerned with the study of meaning.
Expressions such as these can cause miscommunications, misunderstandings, and basically just a lot of confusion.
C. Bizer, J. Lehmann, G. Kobilarov, S. Auer, C. Becker, R. Cyganiak, and S. Hellmann. Dbpedia – a crystallization point for the web of data. Web Semantics: Science, Services and Agents on the WWW, September 2009.