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Bootstrapped Lexicon of English Verbal Polarity Shifters

DOI

This repository contains the data created as part of:

Marc Schulder, Michael Wiegand, Josef Ruppenhofer and Benjamin Roth (2017). "Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features". Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP), pages 624–633, Taipei, Taiwan, 27 November – 3 December 2017.

Content

We provide a bootstrapped lexicon of English verbal polarity shifters. Our lexicon covers 3043 verbs of WordNet v3.1 (Miller et al., 1990) that are single word or particle verbs. Polarity shifter labels are given for each word lemma.

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Data

The data consists of:

  1. Two lists of WordNet verbs (Miller et al., 1990), annotated for whether they cause shifting.
    1. The initial gold standard (§2) of 2000 randomly chosen verbs.
    2. The bootstrapped 1043 verbs (§5.3) that were labelled as shifters by our best classifier and then manually annotated.
  2. Data set of verb phrases from the Amazon Product Review Data corpus (Jindal & Liu, 2008), annotated for polarity of phrase and polar noun.

1. Verbal Shifters

Files

  • The initial gold standard: verbal_shifters.gold_standard.txt
  • The bootstrapped verbs: verbal_shifters.bootstrapping.txt

Format

  • Each line contains a verb and its label, separate by a whitespace.
  • Multiword expressions are separated by an underscore (WORD_WORD).
  • All labels were assigned by an expert annotator.

2. Sentiment Verb Phrases

Files

  • All annotated verb phrases: sentiment_phrases.txt

Content

The file starts with 400 phrases containing shifter verbs, followed by 2231 phrases containing non-shifter verbs.

Format

Every item consists of:

  • The sentence from which the VP and the polar noun were extracted.
  • The VP, polar noun and the verb heading the VP.
  • Constituency parse for the VP.
  • Gold labels for VP and polar noun by a human annotator.
  • Predicted labels for VP and polar noun by RNTN tagger (Socher et al., 2013) and LEX_gold approach.
  • Items are separated by a line of asterisks (*)

Attribution

This data set is published under Creative Commons Attribution 4.0.

If you use it in your research or work, please cite the publication (see above).

BibTex

@inproceedings{schulder2017shifter,
  title={Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features},
  author={Schulder, Marc and Wiegand, Michael and Ruppenhofer, Josef and Roth, Benjamin},
  booktitle={Proceedings of the Eighth International Joint Conference on Natural Language Processing},
  year={2017},
  publisher={Asian Federation of Natural Language Processing},
  volume={1},
  pages={624--633},
  address={Taipei, Taiwan},
  url={http://aclweb.org/anthology/I17-1063}
}

Acknowledgements

This work was partially supported by the German Research Foundation (DFG) under grants RU 1873/2-1 and WI4204/2-1.

References

G. Miller, R. Beckwith, C. Fellbaum, D. Gross, K. Miller: "Introduction to WordNet: An On-Line Lexical Database". International Journal of Lexicography, 3:235-244, 1990.

N. Jindal and B. Liu: "Opinion Spam and Analysis", in Proceedings of ACM-WSDM, 2008.

R. Socher, A. Perelygin, J. Wu, J. Chuang, C. Manning, A. Ng, C. Potts: "Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank", in EMNLP, 2013.

About

Supplementary data for the IJCNLP 2017 paper "Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features" by Schulder, Wiegand, Ruppenhofer and Roth.

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