99 citations · 116 across the 10 of their papers we have counts for
7 papers · 1 filter
BLEU is Not Suitable for the Evaluation of Text Simplification
Elior Sulem, Omri Abend, Ari Rappoport
BLEU is widely considered to be an informative metric for text-to-text generation, including Text Simplification (TS). TS includes both lexical and structural aspects. In this pape…
Simple and Effective Text Simplification Using Semantic and Neural Methods
Elior Sulem, Omri Abend, Ari Rappoport
Sentence splitting is a major simplification operator. Here we present a simple and efficient splitting algorithm based on an automatic semantic parser. After splitting, the text i…
Semantic Structural Evaluation for Text Simplification
Elior Sulem, Omri Abend, Ari Rappoport
Current measures for evaluating text simplification systems focus on evaluating lexical text aspects, neglecting its structural aspects. In this paper we propose the first measure…
Universal Dependency Parsing with a General Transition-Based DAG Parser
Daniel Hershcovich, Omri Abend, Ari Rappoport
This paper presents our experiments with applying TUPA to the CoNLL 2018 UD shared task. TUPA is a general neural transition-based DAG parser, which we use to present the first exp…
Computing Word Classes Using Spectral Clustering
Effi Levi, Saggy Herman, Ari Rappoport
Clustering a lexicon of words is a well-studied problem in natural language processing (NLP). Word clusters are used to deal with sparse data in statistical language processing, as…
SemEval 2019 Shared Task: Cross-lingual Semantic Parsing with UCCA - Call for Participation
Daniel Hershcovich, Leshem Choshen, Elior Sulem +3
We announce a shared task on UCCA parsing in English, German and French, and call for participants to submit their systems. UCCA is a cross-linguistically applicable framework for…