Summary of the paper

Title Improving corpus annotation productivity: a method and experiment with interactive tagging
Authors Atro Voutilainen
Abstract Corpus linguistic and language technological research needs empirical corpus data with nearly correct annotation and high volume to enable advances in language modelling and theorising. Recent work on improving corpus annotation accuracy presents semiautomatic methods to correct some of the analysis errors in available annotated corpora, while leaving the remaining errors undetected in the annotated corpus. We review recent advances in linguistics-based partial tagging and parsing, and regard the achieved analysis performance as sufficient for reconsidering a previously proposed method: combining nearly correct but partial automatic analysis with a minimal amount of human postediting (disambiguation) to achieve nearly correct corpus annotation accuracy at a competitive annotation speed. We report a pilot experiment with morphological (part-of-speech) annotation using a partial linguistic tagger of a kind previously reported with a very attractive precision-recall ratio, and observe that a desired level of annotation accuracy can be reached by using human disambiguation for less than 10\% of the words in the corpus.
Topics Corpus (creation, annotation, etc.), Part of speech tagging, Language modelling
Full paper Improving corpus annotation productivity: a method and experiment with interactive tagging
Bibtex @InProceedings{VOUTILAINEN12.393,
  author = {Atro Voutilainen},
  title = {Improving corpus annotation productivity: a method and experiment with interactive tagging},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
 }
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