QUICK START

Run the follow commands to quickly setup and lunch

1. setup

git clone [email protected]:AcademiaSinicaNLPLab/SinicaSemanticParser.git cd SinicaSemanticParser ./setup.sh

2. run servers

	```shell
cd system
./java_server.sh
./python_server.sh 	## need another terminal

3. test if it works

./batch_run.sh ```

4. for Pythoners

from SinicaConcept.py import SinicaConcept sc = SinicaConcept(host="localhost", port=29999, verbose=True) sents = sc.load_txt(path='../input/input.txt') conceptsAll = sc.parseAll(sents) print conceptsAll ```

INTRODUCTION

System for SenticNet Semantic analysis Challenge Task#2. The system is supposed to take input in the form of a text file and produce "concepts" extracted from each of the sentence in the required format mentioned at the challenge website (http://sentic.net/challenge/).

DOWNLOADING and UNZIPPING

If you have directly downloaded it from github, you should have got 'SinicaSemanticParser-master.zip'. Please unzip it and rename the resulting directory to 'SinicaSemanticParser'.

Or you can just use git clone [email protected]:shafqatvirk/SinicaSemanticParser.git to clone the entrie repository.

REQUIRMENTS

The system requires at least Java, Python, Stanford Parser, and apache-opennlp. The system has been tested with the following configurations:

1. Windows 7

   • Java version 1.7 update 45
   • Python 2.7.5

2. Windows 8

   • Java version 1.7 update 55
   • Python 2.7.5

3. Mac

   • Java version 1.8.0
   • Python 2.7.5

4. Linux (ubuntu 12.04)

   • Java 1.7 update 55
   • Python 2.7.3

FOLDER CONTENTS

This directory 'SinicaSemanticParser' contains the following directries:

1. classifier
2. data
3. headFinder
4. input
5. models
6. output
7. shared
8. system
9. temp
10. tools

INSTRUCTIONS TO RUN THE SYSTEM

A fast way to setup this system for Linux/Mac users:

• run: ./setup.sh and jump to step 4 below to lunch the server!

---

If you run on windows or prefer to manually insatll everything:

1. Please download Stanford Parser version 3.3.1 from this link, extract it and put the resulting stanford-parser-full-2014-01-04 directory in the SinicaSemanticParser directory.

2. Please download apache-opennlp-1.5.3-bin.zip from here, extract it and put the resulting apache-opennlp-1.5.3 directory in the SinicaSemanticParser directory.

   Note: Make sure after unzipping you get the directries named stanford-parser-full-2014-01-04 and apache-opennlp-1.5.3. We have observed depening on how to unzip it, you might get stanford-parser-full-2014-01-04/stanford-parser-full-2014-01-04 and apache-opennlp-1.5.3-bin/apache-opennlp-1.5.3.

   In such cases just copy the stanford-parser-full-2014-01-04 and apache-opennlp-1.5.3 to SinicaSemanticParser directory.

3. From the command prompt go into the 'SinicaSemanticParser/system' directory and compile java programs with the following command:

   1. for windows

   javac -cp .;..\stanford-parser-full-2014-01-04\stanford-parser.jar;..\stanford-parser-full-2014-01-04\stanford-parser-3.3.1-models.jar;..\classifier\maxent\lib\trove-3.0.3.jar;..\apache-opennlp-1.5.3\lib\opennlp-maxent-3.0.3.jar *.java

   2. for __Linux__, __Mac__
   
   	```
   javac -cp .:../stanford-parser-full-2014-01-04/stanford-parser.jar:../stanford-parser-full-2014-01-04/stanford-parser-3.3.1-models.jar:../classifier/maxent/lib/trove-3.0.3.jar:../apache-opennlp-1.5.3/lib/opennlp-maxent-3.0.3.jar *.java
   

4. Now run the ConceptExtractorServer with the following command:

   1. for windows

   java -cp .;..\stanford-parser-full-2014-01-04\stanford-parser.jar;..\stanford-parser-full-2014-01-04\stanford-parser-3.3.1-models.jar;..\classifier\maxent\lib\trove-3.0.3.jar;..\apache-opennlp-1.5.3\lib\opennlp-maxent-3.0.3.jar ConceptExtractorServer

   
   2. for __Linux__, __Mac__
   
   	```
   java -cp .:../stanford-parser-full-2014-01-04/stanford-parser.jar:../stanford-parser-full-2014-01-04/stanford-parser-3.3.1-models.jar:../classifier/maxent/lib/trove-3.0.3.jar:../apache-opennlp-1.5.3/lib/opennlp-maxent-3.0.3.jar ConceptExtractorServer
   

   You should see the following message:

   Loading parser from serialized file edu/stanford/nlp/models/lexparser/englishPCF G.ser.gz ... done [2.4 sec]. Server Initialized, Waiting for input...

   Leave this server running.

5. Open another command line terminal (or split a new panel in tmux), go into the SinicaSemanticParser/system/ directory and start featureExtractorServer by using the following command:

python featureExtractorServer.py

	You should see the following message:

	> "Loading...
	> Ready!"

	Leave this server running

6. Now place your input file in the `SinicaSemanticParser/input/` directory and name it **input.txt** (the input.txt should have one sentence per line)

7. Open another command line terminal, go into the `SinicaSemanticParser/system` directory and run the `ConceptExtractorBatchClient` by issuing the following command:

	```
	java -cp .:../stanford-parser-full-2014-01-04/stanford-parser.jar:../stanford-parser-full-2014-01-04/stanford-parser-3.3.1-models.jar:../classifier/maxent/lib/trove-3.0.3.jar:../apache-opennlp-1.5.3/lib/opennlp-maxent-3.0.3.jar ConceptExtractorBatchClient
	```

	If everything goes well, you should see the following message:

	> "SocketClient initialized
	> Processing......
	> Done!"

8. The output has been stored in the `SinicaSemanticParser/output/output.txt`.