Neural Tagger for MD and NER

This repo contains the software that was used to conduct the experiments reported in our article titled "Improving Named Entity Recognition by Jointly Learning to Disambiguate Morphological Tags" [1] to be presented at COLING 2018.

Tag sentences

This project do not have a designated tagger script for now but you can obtain the output in eval_dir. You should provide the text in tokenized form in CoNLL format. The script will tag both the development and testing files and produce files in ./evaluation/temp/eval_logs/. If you need this and want to contribute by coding and sharing it with the project, you are welcome.

How to run using Docker

1. Clone the repo

git clone https://github.com/BOUN-TABILab-TULAP/NER.git

2. Launch a terminal in the root directory of the repo and build the Docker image where

• -t is the tag for the Docker image. You can provide any name you want
• . is the relative path to the Dockerfile

docker build -t ner .

3. Run the Docker image where

• -d indicates "detach", let the container run in the background
• -p 8080:8080 indicates mapping port 8080 of the container to the port 8080 of the host.

docker run -d -p 8080:8080 ner

4. Send a POST request

• via curl

  curl -X POST http://localhost:8080/ner/predict/ 
  -H 'Content-Type: application/json' 
  -d "{'text':'İstanbul'daki maçta Demet ile Ahmet değişerek oynadı.'}"
  
  > {'dataset_file_string': {'0': ["İstanbul'daki", '_', 'i̇stanbul+Noun+Prop+A3sg+Pnon+Loc^DB+Adj+Rel', 'O'], '1': ['maçta', '_', 'maç+Noun+A3sg+Pnon+Loc', 'O'], '2': ['Demet', '_', 'demet+Noun+A3sg+Pnon+Nom', 'demet+Noun+Prop+A3sg+Pnon+Nom', 'O'], '3': ['ile', '_', 'il+Noun+A3sg+Pnon+Dat', 'ile+Conj', 'ile+Postp+PCNom', 'O'], '4': ['Ahmet', '_', 'ahmet+Noun+Prop+A3sg+Pnon+Nom', 'O'], '5': ['değişerek', '_', 'değ+Verb+Recip+Pos^DB+Adverb+ByDoingSo', 'değiş+Verb+Pos^DB+Adverb+ByDoingSo', 'O'], '6': ['oynadı', '_', 'oyna+Verb+Pos+Past+A3sg', 'O'], '7': ['.', '_', '.+Punc', 'O']}, 'tagger_output': {'0': ["İstanbul'daki", 'B-LOC'], '1': ['maçta', 'O'], '2': ['Demet', 'B-PER'], '3': ['ile', 'O'], '4': ['Ahmet', 'B-PER'], '5': ['değişerek', 'O'], '6': ['oynadı', 'O'], '7': ['.', 'O']}}

• via Python's requests library

  import requests
  res = requests.post('http://localhost:8080/ner/predict/', json={'text':"İstanbul'daki maçta Demet ile Ahmet değişerek oynadı."})
  print(res.json())
  
  > {'dataset_file_string': {'0': ["İstanbul'daki", '_', 'i̇stanbul+Noun+Prop+A3sg+Pnon+Loc^DB+Adj+Rel', 'O'], '1': ['maçta', '_', 'maç+Noun+A3sg+Pnon+Loc', 'O'], '2': ['Demet', '_', 'demet+Noun+A3sg+Pnon+Nom', 'demet+Noun+Prop+A3sg+Pnon+Nom', 'O'], '3': ['ile', '_', 'il+Noun+A3sg+Pnon+Dat', 'ile+Conj', 'ile+Postp+PCNom', 'O'], '4': ['Ahmet', '_', 'ahmet+Noun+Prop+A3sg+Pnon+Nom', 'O'], '5': ['değişerek', '_', 'değ+Verb+Recip+Pos^DB+Adverb+ByDoingSo', 'değiş+Verb+Pos^DB+Adverb+ByDoingSo', 'O'], '6': ['oynadı', '_', 'oyna+Verb+Pos+Past+A3sg', 'O'], '7': ['.', '_', '.+Punc', 'O']}, 'tagger_output': {'0': ["İstanbul'daki", 'B-LOC'], '1': ['maçta', 'O'], '2': ['Demet', 'B-PER'], '3': ['ile', 'O'], '4': ['Ahmet', 'B-PER'], '5': ['değişerek', 'O'], '6': ['oynadı', 'O'], '7': ['.', 'O']}}

References

[1] Gungor, O., Uskudarli, S., Gungor, T., Improving Named Entity Recognition by Jointly Learning to Disambiguate Morphological Tags, 2018, COLING 2018, 19-25 August, (to appear).