The materials science procedural text corpus: Annotating materials synthesis procedures with shallow semantic structures
Materials science literature contains millions of materials synthesis procedures described in
unstructured natural language text. Large-scale analysis of these synthesis procedures …
unstructured natural language text. Large-scale analysis of these synthesis procedures …
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 …
aspects, neglecting its structural aspects. In this paper we propose the first measure to …
[PDF][PDF] Natural language processing
J Eisenstein - Jacob Eisenstein, 2018 - princeton-nlp.github.io
The goal of this text is focus on a core subset of the natural language processing, unified by
the concepts of learning and search. A remarkable number of problems in natural language …
the concepts of learning and search. A remarkable number of problems in natural language …
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 …
semantic representation, which builds on extensive typological work and supports rapid …
A siamese neural network for learning semantically-informed sentence embeddings
Semantic representation is a way of expressing the meaning of a text that can be processed
by a machine to serve a particular natural language processing (NLP) task that usually …
by a machine to serve a particular natural language processing (NLP) task that usually …
Sentiment analysis based on rhetorical structure theory: Learning deep neural networks from discourse trees
Prominent applications of sentiment analysis are countless, covering areas such as
marketing, customer service and communication. The conventional bag-of-words approach …
marketing, customer service and communication. The conventional bag-of-words approach …
Emotion classification in texts over graph neural networks: Semantic representation is better than syntactic
Social media is a widely used platform that provides a huge amount of user-generated
content that can be processed to extract information about users' emotions. This has …
content that can be processed to extract information about users' emotions. This has …
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 …
tremendous practical value in allowing learning for one task to benefit from generalizations …
On the limitations of dataset balancing: The lost battle against spurious correlations
Recent work has shown that deep learning models in NLP are highly sensitive to low-level
correlations between simple features and specific output labels, leading to overfitting and …
correlations between simple features and specific output labels, leading to overfitting and …
The Alexa meaning representation language
This paper introduces a meaning representation for spoken language understanding. The
Alexa meaning representation language (AMRL), unlike previous approaches, which factor …
Alexa meaning representation language (AMRL), unlike previous approaches, which factor …