SemEval 2016

Minions, a team formed of first year stu- dents in the Master of Computational Lin- guistics, started the participation at Semeval-2016 as a semester project, aiming to build a model …...

We report the findings of the Complex Word Identification task of SemEval 2016. To cre- ate a dataset, we conduct a user study with 400 non-native English speakers, and find …...

This paper describes the SemEval 2016 shared task on Aspect Based Sentiment Analysis (ABSA), a continuation of the respective tasks of 2014 and 2015. In its third year, the task …...

In this paper, a system for semantic tex- tual similarity, which participated in Task- 1 in SemEval 2016 (monolingual and cross- lingual sub-tasks) is described. The system contains a preprocessing …...

This paper presents the participation of the TALN team in the Complex Word Identifica- tion Task of SemEval-2016 (Task 11). The purpose of the task was to determine if a …...

We present a system for taxonomy construc- tion that reached the first place in all sub- tasks of the SemEval 2016 challenge on Tax- onomy Extraction Evaluation. Our simple yet …...

We participated in the shared task on mean- ing representation parsing (Task 8 at SemEval- 2016) with the aim of investigating whether we could use Boxer, an existing open-domain semantic …...

This paper describes our submission to the SemEval-2016 Taxonomy Extraction Evalua- tion (TExEval-2) Task. We examine the en- docentric nature of hyponyms and propose a simple rule-based method to identify …...

This paper describes the VCU systems that participated in the Semantic Taxonomy En- richment task of SemEval 2016. The three systems are unsupervised and relied on dictionary-based similarity measures. The …...

AbstractSentiment lexicon is an important tool for identifying the sentiment polarity of words and texts. How to automatically construct sentiment lexicons has become a research topic in the field of …...