Named-Entity-Recognition

July 18, 2018 ยท View on GitHub

We have created a dataset of Hindi-English Code-Mixed Social Media Text (tweets) for the task of Named Entity Recognition. Tweets are pre-processed and annotated as per the 6 NER tags and a 7th Other tag.

NER-Tags

  • B-Per Indicates the Begening of a Person's name.
  • I-Per Indicates the intermediate of a Person's name.
  • B-Org Indicates the Begening of a Organizations's name.
  • I-Org Indicates the intermediate of a Organizations's name.
  • B-Loc Indicates the Begening of a Locations's name.
  • I-Loc Indicates the intermediate of a Locations's name.
  • Other Indicates all the word not falling in any of the above 6.

eg:

#Word#Tag
BharatB-Loc
keOther
2016Other
keOther
DemonetizationOther
meinOther
kitnaOther
kalaOther
dhanOther
realOther
meinOther
aayaOther
???Other
AcchaOther
huaOther
yeOther
prashnaOther
MissB-Per
WordI-Per
ChillarI-Per
koOther
nahiOther
pucchaOther
gayaOther
0Other
#misschillarB-Per
#missworldOther
#DemonetisationOther
#notebandiOther
#modiB-Per
#bjpB-Org
#gujratB-Loc

Contents

  • TwitterData folder contains Id's of the scrapped tweets inside Scrapped folder, and processed and annotated data as named inside this.
  • All the three Models.py are the files for the three ML classification models we used for our reserach paper.
  • preprocessing and vector creation scripts are added with names indicating that.
  • This dataset is in development and in future we will extend this to more number of tweets so as to make it a more reliable dataset for this taska and others.

Outputs

  • DecisionTree and CRF models have direct score calls that gives all the required stats.
  • Keras does not provide the same for displaying score stats for LSTM model, so we build a coustom call of all the measure values and took average over all the iterations (here 5).
  • All the models performed well on the given data.
  • Decision Tree model with a f1-score of 0.94.
  • Conditional Random Field (CRF) model with a f1-score of 0.95.
  • LSTM model with a f1-score of 0.95.

Authors
  • Vinay Singh
  • Deepanshu Vijay
  • Syed A. Sarfaraz
  • Manish Srivastava

LTRC IIIT-Hyderabad


Citation

Named Entity Recognition for Hindi-English Code-Mixed Social Media Text

2018, 27-35, Proceedings of the Seventh Named Entities Workshop here