## 9 Conclusions and Future Work
: _Ambiguous annotations in provided sentences._  
There are many sentences that are strictly assigned to specific categories in the provided restaurant reviews dataset (SemEval-2016 ABSA Task 5). For example, the fourth sentence, \"I liked the atmosphere very much but the food was not worth the price.\" in Table 12 is annotated with the categories \"AMBIENCE#GENERAL\", \"FOOD#PRICES\", and \"FOOD#QUALITY\", whereas our predicted categories are \"AMBIENCE#GENERAL\", and \"FOOD#QUALITY\", \"RESTAURANT#PRICES\". Although, our system successfully predicted two out of the three classes, the ACD model was confused between the \"RESTAURANT#PRICES\" and \"FOOD#PRICES\" categories. The next sentence, \"It is not worth going at all and spend your money there!!! !\" is also annotated with the category of \"RESTAURANT#GENERAL\", whereas our predicted categories are \"RESTAURANT#GENERAL\", and \"RESTAURANT#PRICES\". Our system returned categories that are partially correct, because it predicted \"RESTAURANT#PRICES\" due to the presence of the word \"money\" in the sentence. Consequently, due to the existence of such ambiguities it is difficult to accurately categorize sentiment. Even humans can sometimes be confused if such ambiguous tagging exists. Each single review from a restaurant dataset consists of multiple sentences (or a paragraph) where each sentence is labeled with aspect categories. Sometimes understanding an individual review sentence depends on the prior sentences. Incorporating the context in a sentence helps reduce the ambiguities caused by the presence of personal pronouns and inadequate information. We can solve this problem by replacing personal pronouns (e.g., it, they) with suitable reference (or noun) words from the contextual sentence(s). The link between personal pronouns and the context noun words can be mapped by using dependency parsing. Successful substitution of personal pronouns with proper meaningful words in a sentence will reduce the misclassification rate. For example, Sentence 1, \"Don't leave the restaurant without it\" is incorrectly labeled by our system which contains a personal pronoun \"it\" and Sentence 2, \"Green Tea creme brulee is a must!\" is the previous sentence of Sentence 1. In Sentence 2 the term, \"Green Tea creme brulee\" is referring to a personal pronoun in Sentence 1. So, if we substitute the term \"it\" with, \"Green Tea creme brulee\", then Sentence 1 will look like, \"Don't leave the restaurant without Green Tea creme brulee\" as shown in Figure 7. This type of pre-processing must be done before presenting a sentence to the system to avoid personal pronoun ambiguities. \begin{table}
\begin{tabular}{c c} \hline \hline
**Sentence** & **Predicted Category** & **Actual Category** \\ \hline It is the not worth going at all and spend & [“RESTAURANT#GENERAL”, & [“RESTAURANT#GENERAL”] \\ your money there!!!! & \"RESTAURANT#PRICES”] & [“RESTAURANT#GENERAL”] \\ \hline Mama Mia—I live in the neighborhood & [“AMBIENCE#GENERAL”, & [“RESTAURANT#GENERAL”] \\ and feel lucky to live by such a great & \"RESTAURANT#GENERAL”] & [“RESTAURANT#GENERAL”] \\ \hline Its worth the wait, especially since they’ll & [“SERVICE#GENERAL”] & [“RESTAURANT#GENERAL”, \\ give you a call when the table is ready. & [“SERVICE#GENERAL”] & [“SERVICES#GENERAL”] \\ \hline I liked the atmosphere very much but the & [“AMBIENCE#GENERAL”, & [“AMBIENCE#GENERAL”, \\ food was not worth the price. & \"FOOD#PRICES”, \"RESTAURANT#PRICES”] & “FOOD#QUALITY”] \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Annotation ambiguities. **Author Contributions:** This research work is the collaborative effort of a team. The idea was conceived by [PERSON], [PERSON] and [PERSON]. The simulations were carried out by [PERSON], [PERSON], [PERSON] and [PERSON]. The manuscript was written by [PERSON], [PERSON], [PERSON] and [PERSON]. [PERSON] has discussed the idea in the context of smart cities and significantly improved the document after proof reading.