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. This paper studies the problem of mining relational data hidden in natural language text. In particular, it approaches the relation classification problem with the strategy of transductive learning. Dif- …...

This paper presents the UNITOR system that participated to the SemEval 2012 Task 6: Se- mantic Textual Similarity (STS). The task is here modeled as a Support Vector (SV) regres- …...

We present an unsupervised method to find lexical variations in Roman Urdu informal text. Our method includes a phonetic algorithm UrduPhone, a feature- based similarity function, and a clustering algorithm …...

Coreference resolution for event men- tions enables extraction systems to process document-level information. Current sys- tems in this area base their decisions on rich semantic features from various knowledge bases, …...

AbstractRule-based models are attractive for various tasks because they inherently lead to interpretable and explainable decisions and can easily incorporate prior knowledge. However, such systems are difficult to apply to …...

AbstractEven if recent Transformer-based architectures, such as BERT, achieved impressive results in semantic processing tasks, their fine-tuning stage still requires large scale training resources. Usually, Data Augmentation (DA) techniques can …...

AbstractRound-trip Machine Translation (MT) is a popular choice for paraphrase generation, which leverages readily available parallel corpora for supervision. In this paper, we formalize the implicit similarity function induced by …...