99 citations · 330 across the 75 of their papers we have counts for
10 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…
Comprehensive Supersense Disambiguation of English Prepositions and Possessives
Nathan Schneider, Jena D. Hwang, Vivek Srikumar +6
Semantic relations are often signaled with prepositional or possessive marking--but extreme polysemy bedevils their analysis and automatic interpretation. We introduce a new annota…
Reference-less Measure of Faithfulness for Grammatical Error Correction
Leshem Choshen, Omri Abend
We propose USim, a semantic measure for Grammatical Error Correction (GEC) that measures the semantic faithfulness of the output to the source, thereby complementing existing refer…