Towards Syntactic Iberian Polarity Classification DV was funded by MECD (FPU13/01180). MG is funded by a Juan de la Cierva grant (FJCI-2014-22853). CGR has received funding from the ERC, under the European Union’s Horizon 2020 research and innovation programme (FASTPARSE, grant agreement No 714150). This research was supported by MINECO (FFI2014-51978-C2).
Table 4: Results of the different tests. In LKit we only evaluated the positive and negative results (it also classifies sentences with no polarity).
['[BOLD] Lg', '[BOLD] SL-O', '[BOLD] SL+O', '[BOLD] ML-O', '[BOLD] ML+O', '[BOLD] LKit']
The baseline (SL-O) obtained values between 54% (ca) and 62.95% (eu), results that are in line to those obtained by the supervised model. As we are not aware of available sa tools for ca, we could not compare our results with other systems. For Basque, San Vicente and Saralegi They used a simple average polarity ratio classifier, which is similar to our baseline. Even if the lexica are different, their results are very similar to our SL-O system (63% vs 62,95%), and they also show that manually reviewing the lexica can boost the accuracy by up to 13%. In gl and pt the best values were obtained using individual lexica together with syntactic rules, while the Iberian system achieved the best results in the other languages.