Changes between Version 12 and Version 13 of private/NlpInPracticeCourse/InformationExtraction

Timestamp:

Nov 15, 2017, 7:15:05 PM (6 years ago)

Author:

Zuzana Nevěřilová

Comment:

--

private/NlpInPracticeCourse/InformationExtraction

@@ -3 +3 @@
 [[https://is.muni.cz/auth/predmet/fi/ia161|IA161]] [[en/AdvancedNlpCourse|Advanced NLP Course]], Course Guarantee: Aleš Horák
 
-Prepared by: Vojtěch Kovář
+Prepared by: Zuzana Nevěřilová
 
 
@@ -38 +38 @@
    * change {{{markupAware}}} to {{{false}}}
    * change {{{sourceUrl}}} to {{{stringContent}}} and paste some news text
-   * you can find three sample texts here:
+   * you can find three sample texts here: [raw-attachment:text1.txt text1.txt], [raw-attachment:text2.txt text2.txt], [raw-attachment:text3.txt text3.txt]
  1. Create corpus:
    * right click on Language !Resources/New/GATE Corpus in the left menu
@@ -47 +47 @@
 So far, GATE did not much more than Stanford NER in lecture 04. Note, however, that all tokens are annotated and POS-tagged.
 
-We add rules for extracting job titles and the respective person names:
+We add rules for extracting job titles and the respective person names. The rules are defined in the grammars [raw-attachment:jobtitle.jape] and [raw-attachment:jobtitleperson.jape]
 
  1. Right click Processing !Resources/New/JAPE Transducer in the left menu
@@ -56 +56 @@
  1. Observer the grammars {{{jobtitle.jape}}} and {{{jobtitleperson.jape}}}
 
-Add new grammar {{{jobtitleperson.jape}}} and observe the results.
+Add new transducer with the grammar {{{jobtitleperson.jape}}} and observe the results.
 
 Optionally, you can add further documents and observe how universal the {{{jobtitleperson.jape}}} grammar is.
 
 Write your observations to {{{<YOUR_FILE>}}}.
-
-
-You may modify or draw inspiration from [raw-attachment:demo.py this demo script].