Rodrigo Agerri

Software

  1. IXA pipes: Ready to use NLP tools
  2. Opinion Target Extraction at SemEval 2015
  3. QWN-PPV: Q-WordNet via Personalized PageRank

IXA pipes: Ready to use NLP tools

IXA pipes is a modular set of Natural Language Processing tools (or pipes) which provide easy access to NLP technology for several languages. It offers robust and efficient linguistic annotation to both researchers and non-NLP experts with the aim of lowering the barriers of using NLP technology either for research purposes or for small industrial developers and SMEs. The IXA pipes can be used or exploit its modularity to pick and change different components.

If you use ixa-pipe-nerc for Named Entity Tagging, please cite this paper:

If you use other IXA pipes tools or the models, please cite this paper:

Opinion Target Extraction at SemEval 2015

We participated in Aspect Based Sentiment Analysis task at SemeEval 2015, obtaining best results in the Opinion Target Extraction (OTE) subtask.

We address the OTE task as a sequence labeling problem. We use the ixa-pipe-ote system off-the-shelf to train our OTE models; ixa-pipe-ote uses the Apache OpenNLP project implementation of the Perceptron algorithm customized with its own local and word representation features.

If you use the system, please the following paper:

QWN-PPV: Q-WordNet via Personalized PageRank

A new Q-WordNet version based on applying Personalized PageRanking to the original Q-WordNet approach. It is a simple, robust and (almost) unsupervised dictionary-based method (Q-WordNet by Personalized PageRanking Vector) to automatically generate polarity lexicons.

The extrinsic evaluations performed show that qwn-ppv outperforms other automatically generated lexicons. It also shows very competitive and robust results with respect to manually annotated ones. Results suggest that no single lexicon is best for every task and dataset and that the intrinsic evaluation of polarity lexicons is not a good indicator of good performance on a Sentiment Analysis task.

Our method is easily applicable to create qwn-ppv(s) other languages, and we demonstrate it by providing polarity lexicons for English and Spanish. The qwn-ppv method allows to easily create quality polarity lexicons whenever no domain-based annotated corpora are available for a given language.