= Named Entity Recognition =

[[https://is.muni.cz/auth/predmet/fi/ia161|IA161 Advanced NLP Course]], Course Guarantee: Aleš Horák

Prepared by: Zuzana Nevěřilová

== TODO til 31.5.2015 ==

 1. choose particular papers for [[#References|References]] below (that will serve as input for the lecture later on)
 1. prepare the [[#PracticalSession|Practical Session]]

== State of the Art ==

=== References ===

 1. David Nadeau, Satoshi Sekine: A survey of named entity recognition and classification. In Satoshi Sekine and Elisabete Ranchhod (eds.) Named Entities: Recognition, classification and use. Lingvisticæ Investigationes 30:1. 2007. pp. 3–26 [[http://brown.cl.uni-heidelberg.de/~sourjiko/NER_Literatur/survey.pdf]]
 1. Charles Sutton and Andrew !McCallum: An Introduction to Conditional Random Fields. Foundations and Trends in Machine Learning 4 (4). 2012. [[http://homepages.inf.ed.ac.uk/csutton/publications/crftut-fnt.pdf]]

== Practical Session ==

Try naive gazetteer method (implement substring search) on prepared data. 
Observe the recognition: 
  1. what happens to every string present in the gazetteer?
  1. what happens to NE not present in the gazetteer?

Try machine learning approach (use the Stanford NER) with prepared data.
Observe the recognition:
  1. measure precision, recall, and F1-score on the test data
  1. find NEs not present in the train data
  1. find NEs that were not recognized
  1. discuss what types of NE are easy/difficult to recognize