SERGIOJIMENEZ at SemEval-2016 Task 1: Effectively Combining Paraphrase Database, String Matching, WordNet, and Word Embedding for Semantic Textual Similarity

SemEval-2013 Task 4: Free Paraphrases of Noun Compounds

In this paper, we describe SemEval-2013 Task 4: the definition, the data, the evaluation and the results. The task is to capture some of the meaning of English noun compounds via paraphrasing. Given a two-word noun compo…

SemEval-2015 Task 1: Paraphrase and Semantic Similarity in Twitter (PIT)

Talla at SemEval-2017 Task 3: Identifying Similar Questions Through Paraphrase Detection

This paper describes our approach to the SemEval-2017 shared task of determining question-question similarity in a community question-answering setting (Task 3B). We extracted both syntactic and semantic similarity featu…

MarSan at SemEval-2022 Task 6: iSarcasm Detection via T5 and Sequence Learners

The paper describes SemEval-2022’s shared task “Intended Sarcasm Detection in English and Arabic.” This task includes English and Arabic tweets with sarcasm and non-sarcasm samples and irony speech labels.The first two s…

Lotus at SemEval-2021 Task 2: Combination of BERT and Paraphrasing for English Word Sense Disambiguation

In this paper, we describe our proposed methods for the multilingual word-in-Context disambiguation task in SemEval-2021. In this task, systems should determine whether a word that occurs in two different sentences is us…