Automated text simplification: a survey
SS Al-Thanyyan, AM Azmi - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Text simplification (TS) reduces the complexity of the text to improve its readability and
understandability, while possibly retaining its original information content. Over time, TS has …
understandability, while possibly retaining its original information content. Over time, TS has …
[PDF][PDF] A fast and accurate dependency parser using neural networks
Almost all current dependency parsers classify based on millions of sparse indicator
features. Not only do these features generalize poorly, but the cost of feature computation …
features. Not only do these features generalize poorly, but the cost of feature computation …
A joint many-task model: Growing a neural network for multiple nlp tasks
Transfer and multi-task learning have traditionally focused on either a single source-target
pair or very few, similar tasks. Ideally, the linguistic levels of morphology, syntax and …
pair or very few, similar tasks. Ideally, the linguistic levels of morphology, syntax and …
Simverb-3500: A large-scale evaluation set of verb similarity
Verbs play a critical role in the meaning of sentences, but these ubiquitous words have
received little attention in recent distributional semantics research. We introduce SimVerb …
received little attention in recent distributional semantics research. We introduce SimVerb …
[BOOK][B] Elements of structural syntax
L Tesnière - 2015 - library.oapen.org
This volume is now finally available in English, sixty years after the death of its author,
Lucien Tesnière. It has been translated from the French original into German, Spanish …
Lucien Tesnière. It has been translated from the French original into German, Spanish …
A survey of syntactic-semantic parsing based on constituent and dependency structures
MS Zhang - Science China Technological Sciences, 2020 - Springer
Syntactic and semantic parsing has been investigated for decades, which is one primary
topic in the natural language processing community. This article aims for a brief survey on …
topic in the natural language processing community. This article aims for a brief survey on …
Neural semantic role labeling with dependency path embeddings
This paper introduces a novel model for semantic role labeling that makes use of neural
sequence modeling techniques. Our approach is motivated by the observation that complex …
sequence modeling techniques. Our approach is motivated by the observation that complex …
[PDF][PDF] Semeval 2015 task 18: Broad-coverage semantic dependency parsing
Abstract Task 18 at SemEval 2015 defines Broad-Coverage Semantic Dependency Parsing
(SDP) as the problem of recovering sentence-internal predicate–argument relationships for …
(SDP) as the problem of recovering sentence-internal predicate–argument relationships for …
[PDF][PDF] A transition-based system for joint part-of-speech tagging and labeled non-projective dependency parsing
Most current dependency parsers presuppose that input words have been morphologically
disambiguated using a part-of-speech tagger before parsing begins. We present a …
disambiguated using a part-of-speech tagger before parsing begins. We present a …
[PDF][PDF] It depends: Dependency parser comparison using a web-based evaluation tool
The last few years have seen a surge in the number of accurate, fast, publicly available
dependency parsers. At the same time, the use of dependency parsing in NLP applications …
dependency parsers. At the same time, the use of dependency parsing in NLP applications …