1.3k citations · 3.2k across the 44 of their papers we have counts for
12 papers · 2 filters
Semi Supervised Preposition-Sense Disambiguation using Multilingual Data
Hila Gonen, Yoav Goldberg
Prepositions are very common and very ambiguous, and understanding their sense is critical for understanding the meaning of the sentence. Supervised corpora for the preposition-sen…
Improving Reliability of Word Similarity Evaluation by Redesigning Annotation Task and Performance Measure
Oded Avraham, Yoav Goldberg
We suggest a new method for creating and using gold-standard datasets for word similarity evaluation. Our goal is to improve the reliability of the evaluation, and we do this by re…
Morphological Inflection Generation with Hard Monotonic Attention
Roee Aharoni, Yoav Goldberg
We present a neural model for morphological inflection generation which employs a hard attention mechanism, inspired by the nearly-monotonic alignment commonly found between the ch…
A Neural Network for Coordination Boundary Prediction
Jessica Ficler, Yoav Goldberg
We propose a neural-network based model for coordination boundary prediction. The network is designed to incorporate two signals: the similarity between conjuncts and the observati…
Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks
Yossi Adi, Einat Kermany, Yonatan Belinkov +2
There is a lot of research interest in encoding variable length sentences into fixed length vectors, in a way that preserves the sentence meanings. Two common methods include repre…
Coordination Annotation Extension in the Penn Tree Bank
Jessica Ficler, Yoav Goldberg
Coordination is an important and common syntactic construction which is not handled well by state of the art parsers. Coordinations in the Penn Treebank are missing internal struct…
Improved Parsing for Argument-Clusters Coordination
Jessica Ficler, Yoav Goldberg
Syntactic parsers perform poorly in prediction of Argument-Cluster Coordination (ACC). We change the PTB representation of ACC to be more suitable for learning by a statistical PCF…
Getting More Out Of Syntax with PropS
Gabriel Stanovsky, Jessica Ficler, Ido Dagan +1
Semantic NLP applications often rely on dependency trees to recognize major elements of the proposition structure of sentences. Yet, while much semantic structure is indeed express…
Improving Hypernymy Detection with an Integrated Path-based and Distributional Method
Vered Shwartz, Yoav Goldberg, Ido Dagan
Detecting hypernymy relations is a key task in NLP, which is addressed in the literature using two complementary approaches. Distributional methods, whose supervised variants are t…
Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations
Eliyahu Kiperwasser, Yoav Goldberg
We present a simple and effective scheme for dependency parsing which is based on bidirectional-LSTMs (BiLSTMs). Each sentence token is associated with a BiLSTM vector representing…
Training with Exploration Improves a Greedy Stack-LSTM Parser
Miguel Ballesteros, Yoav Goldberg, Chris Dyer +1
We adapt the greedy Stack-LSTM dependency parser of Dyer et al. (2015) to support a training-with-exploration procedure using dynamic oracles(Goldberg and Nivre, 2013) instead of c…
Easy-First Dependency Parsing with Hierarchical Tree LSTMs
Eliyahu Kiperwasser, Yoav Goldberg
We suggest a compositional vector representation of parse trees that relies on a recursive combination of recurrent-neural network encoders. To demonstrate its effectiveness, we us…