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# Semantic Composition Edit

8 papers with code · Natural Language Processing

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136

# The Lifted Matrix-Space Model for Semantic Composition

Tree-structured neural network architectures for sentence encoding draw inspiration from the approach to semantic composition generally seen in formal linguistics, and have shown empirical improvements over comparable sequence models by doing so.

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# Semantic Compositional Networks for Visual Captioning

The degree to which each member of the ensemble is used to generate an image caption is tied to the image-dependent probability of the corresponding tag.

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# Table Filling Multi-Task Recurrent Neural Network for Joint Entity and Relation Extraction

This paper proposes a novel context-aware joint entity and word-level relation extraction approach through semantic composition of words, introducing a Table Filling Multi-Task Recurrent Neural Network (TF-MTRNN) model that reduces the entity recognition and relation classification tasks to a table-filling problem and models their interdependencies.

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# From Characters to Time Intervals: New Paradigms for Evaluation and Neural Parsing of Time Normalizations

This paper presents the first model for time normalization trained on the SCATE corpus.

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# A Semantically Compositional Annotation Scheme for Time Normalization

We present a new annotation scheme for normalizing time expressions, such as {}three days ago{''}, to computer-readable forms, such as 2016-03-07.

20

# A Survey on Deep Learning for Named Entity Recognition

22 Dec 2018DA-southampton/ner

NER serves as the basis for a variety of natural language applications such as question answering, text summarization, and machine translation.

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# No Word is an Island -- A Transformation Weighting Model for Semantic Composition

11 Jul 2019sfb833-a3/commix

Composition models of distributional semantics are used to construct phrase representations from the representations of their words.

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