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Edited READE file

Rasoul Kaljahi 5 years ago
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      README.md

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README.md

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-This package contains the Sentiment Expression Annotation (SEA) described in [1]. The SEA annotations are created on the dataset released for task 5 of SemEval 2016 shared task on aspect-based sentiment analysis (ABSA).
+This package contains the **Sentiment Expression Annotation (SEA)** described in [1]. The SEA annotations are created on the dataset released for task 5 of SemEval 2016 shared task on aspect-based sentiment analysis (ABSA).
 
 Due to licensing restrictions, the original data cannot accompany these annotations. As a workaround, an script has been included which takes in the original dataset and attaches the SEA annotations. The script should be used as follows:
 
-python generate-sea.py -x <PATH_TO_ORIGINAL_XML_FILE> -d <DOMAIN> -s <SUBSET> 
+    python generate-sea.py -x -d -s
 
 DOMAIN is either laptop or restaurant and SUBSET is either train or test. For example, assuming that the original XML files have been downloaded into the current directory, the following command generates the annotation files for laptop training set in the current directory:
 
-python generate-sea.py -x ABSA16_Laptops_Train_SB1_v2.xml -d laptop -s train
+    python generate-sea.py -x ABSA16_Laptops_Train_SB1_v2.xml -d laptop -s train
 
 The generated annotation files are as follows:
 
-- train.laptop.at	aspect terms and their polarities one per line, extracted from the XML file
-- train.laptop.aio      SEA annotation in columnar IO tagging format, one token per line, with blank lines separating sentences
+ - train.laptop.at aspect terms and their polarities one per line, extracted from the XML file
+ - train.laptop.aio SEA annotation in columnar IO tagging format, one token per line, with blank lines separating sentences
 
 The SEA annotations in the aio file match the aspect terms in the at file. This means that the first sentences in the aio file is the SEA annotation corresponding to the first aspect term in the at file, and so on.
 
@@ -20,3 +20,5 @@ The annotations are in columnar format where the tokens constituting the sentime
 Note that the original sentences have been tokenized by the script.
 
 [1] Rasoul Kaljahi and Jennifer Foster. Sentiment expression boundaries in sentiment polarity classification. In Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA), 2018.
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