fix url error in rnn_en.rst

doc/howto/deep_model/rnn/rnn_en.rst

@@ -246,6 +246,6 @@ The code is listed below:
     outputs(beam_gen)
 
 
-Notice that this generation technique is only useful for decoder like generation process. If you are working on sequence tagging tasks, please refer to :ref:`sentiment_analysis_en` for more details.
+Notice that this generation technique is only useful for decoder like generation process. If you are working on sequence tagging tasks, please refer to :ref:`semantic_role_labeling_en` for more details.
 
 The full configuration file is located at :code:`demo/seqToseq/seqToseq_net.py`.

doc/tutorials/semantic_role_labeling/index_en.md

+```eval_rst
+..  _semantic_role_labeling_en:
+```
+
 # Semantic Role labeling Tutorial #
 
 Semantic role labeling (SRL) is a form of shallow semantic parsing whose goal is to discover the predicate-argument structure of each predicate in a given input sentence. SRL is useful as an intermediate step in a wide range of natural language processing tasks, such as information extraction. automatic document categorization and question answering.  An instance is as following [1]:

doc/tutorials/sentiment_analysis/index_en.md

-```eval_rst
-..  _sentiment_analysis_en:
-```
-
 # Sentiment Analysis Tutorial
 
 Sentiment analysis has many applications. A basic task in sentiment analysis is classifying the polarity of a given text at the document, sentence or feature/aspect level. One simple example is to classify the customer reviews in a shopping website, a tourism website, and group buying websites like Amazon, TaoBao, Tmall etc.