ASAP: Automatic Semantic Alignment for Phrases



In this paper we describe the ASAP system (Automatic Semantic Alignment for Phrases) which participated on the Task 1 at the SemEval-2014 contest (Marelli et al., 2014a). Our assumption is that STS (Semantic Text Similarity) follows a function considering lexical, syntactic, semantic and distributional features. We demonstrate the learning process of this function without any deep preprocessing achieving an acceptable correlation.


Semantic Similarity, NLP, WordNet

Related Project

Crowds - Understanding urban land use from digital footprints of crowds


SemEval Workshop, COLING 2014, Ireland, August 2014


Cited by

Year 2017 : 2 citations

 Silva, A. D. B. (2017). O uso de recursos linguísticos para mensurar a semelhança semântica entre frases curtas através de uma abordagem híbrida.

 Kadupitiya, J. C. S., Ranathunga, S., & Dias, G. (2017, July). Assessment and Error Identification of Answers to Mathematical Word Problems. In 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT) (pp. 55-59). IEEE.

Year 2016 : 4 citations

 Kadupitiya, J. C. S., Ranathunga, S., & Dias, G. (2016). Short Sentence Similarity Calculation using Corpus-Based and Knowledge-Based Similarity Measures. WSSANLP 2016, 44.

 Luisa Bentivogli, Raffaella Bernardi , Marco Marelli, Stefano Menini, Marco Baroni, Roberto Zamparelli. SICK through the SemEval glasses. Lesson learned from the evaluation of compositional distributional semantic models on full sentences through semantic relatedness and textual entailment. Journal of Language Resources and Evaluation. 10.1007/s10579-015-9332-5

 Lu, Wei, et al. "Joint semantic similarity assessment with raw corpus and structured ontology for semantic-oriented service discovery." Personal and Ubiquitous Computing 20.3 (2016): 311-323.

 Kadupitiya, J. C. S., Surangika Ranathunga, and Gihan Dias. "Sinhala Short Sentence Similarity Measures using Corpus-Based Simi-larity for Short Answer Grading." WSSANLP 2016 (2016): 44.

Year 2015 : 4 citations

 Bentivogli, L., Bernardi, R., Marelli, M., Menini, S., Baroni, M., & Zamparelli, R. 2015. SICK Through the SemEval Glasses.

 Yuanyuan Cai, Wei Lu, Xiaoping Che, Kailun Shi. Differential Evolutionary Algorithm Based on Multiple Vector Metrics for
Semantic Similarity Assessment in Continuous Vector Space. 21st International Conference on Distributed Multimedia Systems (DMS'2015).

 Wei Lu, Yuanyuan Cai, Xiaoping Che, and Kailun Shi. 2015. Semantic Similarity Assessment Using Differential Evolution Algorithm in Continuous Vector Space. J. Vis. Lang. Comput. 31, PB (December 2015), 246-251. DOI=

 Cai, Yuanyuan, et al. "Knowledge-Enhanced Multi-semantic Fusion for Concept Similarity Measurement in Continuous Vector Space." Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom), 2015 IEEE 12th Intl Conf on. IEEE, 2015.

Year 2014 : 1 citations

 Marelli, Marco, et al. "Semeval-2014 task 1: Evaluation of compositional distributional semantic models on full sentences through semantic relatedness and textual entailment." SemEval-2014 (2014).