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Universal Conceptual Cognitive Annotation (UCCA)
Syntactic structures, by their nature, reflect first and foremost the formal constructions used for expressing meanings. This renders them sensitive to formal variation both within and acrossExpand
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Learnability-Based Syntactic Annotation Design
There is often more than one way to represent syntactic structures, even within a given formalism. Selecting one representation over another may affect parsing performance. Therefore, selectingExpand
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BLEU is Not Suitable for the Evaluation of Text Simplification
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 paper we show that BLEUExpand
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A Transition-Based Directed Acyclic Graph Parser for UCCA
We present the first parser for UCCA, a cross-linguistically applicable framework for semantic representation, which builds on extensive typological work and supports rapid annotation. UCCA poses aExpand
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Neutralizing Linguistically Problematic Annotations in Unsupervised Dependency Parsing Evaluation
Dependency parsing is a central NLP task. In this paper we show that the common evaluation for unsupervised dependency parsing is highly sensitive to problematic annotations. We show that for threeExpand
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Multitask Parsing Across Semantic Representations
The ability to consolidate information of different types is at the core of intelligence, and has tremendous practical value in allowing learning for one task to benefit from generalizations learnedExpand
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Improved Unsupervised POS Induction through Prototype Discovery
We present a novel fully unsupervised algorithm for POS induction from plain text, motivated by the cognitive notion of prototypes. The algorithm first identifies landmark clusters of words, servingExpand
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Semantic Structural Evaluation for Text Simplification
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 to addressExpand
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Simple and Effective Text Simplification Using Semantic and Neural Methods
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 is amenable forExpand
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SemEval 2019 Task 1: Cross-lingual Semantic Parsing with UCCA
We present the SemEval 2019 shared task on UCCA parsing in English, German and French, and discuss the participating systems and results. UCCA is a cross-linguistically applicable framework forExpand
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