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Found 41 papers, 14 papers with code
DiaASQ : A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis
In this work, we introduce a novel task of conversational aspect-based sentiment quadruple analysis, namely DiaASQ, aiming to detect the sentiment quadruple of target-aspect-opinion-sentiment in a dialogue.
TOE: A Grid-Tagging Discontinuous NER Model Enhanced by Embedding Tag/Word Relations and More Fine-Grained Tags
Concretely, we construct tag representations and embed them into TREM, so that TREM can treat tag and word representations as queries/keys/values and utilize self-attention to model their relationships.
Entity-centered Cross-document Relation Extraction
First, we focus on input construction for our RE model and propose an entity-based document-context filter to retain useful information in the given documents by using the bridge entities in the text paths.
Conversational Semantic Role Labeling with Predicate-Oriented Latent Graph
In this work, we investigate the integration of a latent graph for CSRL.
Joint Alignment of Multi-Task Feature and Label Spaces for Emotion Cause Pair Extraction
We first propose a feature-task alignment to explicitly model the specific emotion-&cause-specific features and the shared interactive feature.
OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extraction
Event extraction (EE) is an essential task of information extraction, which aims to extract structured event information from unstructured text.
Effective Token Graph Modeling using a Novel Labeling Strategy for Structured Sentiment Analysis
The essential label set consists of the basic labels for this task, which are relatively balanced and applied in the prediction layer.
Unified Named Entity Recognition as Word-Word Relation Classification
So far, named entity recognition (NER) has been involved with three major types, including flat, overlapped (aka.
Ranked #2 on
Chinese Named Entity Recognition
on OntoNotes 4
Nonautoregressive Encoder-Decoder Neural Framework for End-to-End Aspect-Based Sentiment Triplet Extraction
Aspect-based sentiment triplet extraction (ASTE) aims at recognizing the joint triplets from texts, i. e., aspect terms, opinion expressions, and correlated sentiment polarities.
Mastering the Explicit Opinion-role Interaction: Syntax-aided Neural Transition System for Unified Opinion Role Labeling
Unified opinion role labeling (ORL) aims to detect all possible opinion structures of 'opinion-holder-target' in one shot, given a text.
A Span-Based Model for Joint Overlapped and Discontinuous Named Entity Recognition
Second, we perform relation classification to judge whether a given pair of entity fragments to be overlapping or succession.
Learn from Syntax: Improving Pair-wise Aspect and Opinion Terms Extractionwith Rich Syntactic Knowledge
In this paper, we propose to enhance the pair-wise aspect and opinion terms extraction (PAOTE) task by incorporating rich syntactic knowledge.
End-to-end Semantic Role Labeling with Neural Transition-based Model
It performs the two subtasks of SRL: predicate identification and argument role labeling, jointly.
Ranked #1 on
Semantic Role Labeling
on CoNLL-2009
Modeling Local Contexts for Joint Dialogue Act Recognition and Sentiment Classification with Bi-channel Dynamic Convolutions
In this paper, we target improving the joint dialogue act recognition (DAR) and sentiment classification (SC) tasks by fully modeling the local contexts of utterances.
HiTrans: A Transformer-Based Context- and Speaker-Sensitive Model for Emotion Detection in Conversations
Emotion detection in conversations (EDC) is to detect the emotion for each utterance in conversations that have multiple speakers.
Ranked #12 on
Emotion Recognition in Conversation
on EmoryNLP
Improving Text Understanding via Deep Syntax-Semantics Communication
Recent studies show that integrating syntactic tree models with sequential semantic models can bring improved task performance, while these methods mostly employ shallow integration of syntax and semantics.
Nominal Compound Chain Extraction: A New Task for Semantic-enriched Lexical Chain
Lexical chain consists of cohesion words in a document, which implies the underlying structure of a text, and thus facilitates downstream NLP tasks.
Aggressive Language Detection with Joint Text Normalization via Adversarial Multi-task Learning
Aggressive language detection (ALD), detecting the abusive and offensive language in texts, is one of the crucial applications in NLP community.
Mimic and Conquer: Heterogeneous Tree Structure Distillation for Syntactic NLP
Syntax has been shown useful for various NLP tasks, while existing work mostly encodes singleton syntactic tree using one hierarchical neural network.
Retrofitting Structure-aware Transformer Language Model for End Tasks
We consider retrofitting structure-aware Transformer-based language model for facilitating end tasks by proposing to exploit syntactic distance to encode both the phrasal constituency and dependency connection into the language model.
High-order Refining for End-to-end Chinese Semantic Role Labeling
Current end-to-end semantic role labeling is mostly accomplished via graph-based neural models.
Cross-lingual Semantic Role Labeling with Model Transfer
In this paper, we fill the gap of cross-lingual SRL by proposing an end-to-end SRL model that incorporates a variety of universal features and transfer methods.
Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification
The idea is to allow the dependency graph to guide the representation learning of the transformer encoder and vice versa.
AMR Parsing with Latent Structural Information
Abstract Meaning Representations (AMRs) capture sentence-level semantics structural representations to broad-coverage natural sentences.
Cross-Lingual Semantic Role Labeling with High-Quality Translated Training Corpus
Many efforts of research are devoted to semantic role labeling (SRL) which is crucial for natural language understanding.
End to End Chinese Lexical Fusion Recognition with Sememe Knowledge
In this paper, we present Chinese lexical fusion recognition, a new task which could be regarded as one kind of coreference recognition.
Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition
Conversational emotion recognition (CER) has attracted increasing interests in the natural language processing (NLP) community.
Ranked #15 on
Emotion Recognition in Conversation
on EmoryNLP
Bacteria Biotope Relation Extraction via Lexical Chains and Dependency Graphs
abstract In this article, we describe our approach for the Bacteria Biotopes relation extraction (BB-rel) subtask in the BioNLP Shared Task 2019.
DLocRL: A Deep Learning Pipeline for Fine-Grained Location Recognition and Linking in Tweets
Recognizing and linking such fine-grained location mentions to well-defined location profiles are beneficial for retrieval and recommendation systems.
Recognizing irregular entities in biomedical text via deep neural networks
We evaluate our models on two datasets for recognizing regular and irreg- ular biomedical entities.
A Bi-LSTM-RNN Model for Relation Classification Using Low-Cost Sequence Features
This model divides a sentence or text segment into five parts, namely two target entities and their three contexts.
Multi-prototype Chinese Character Embedding
Chinese sentences are written as sequences of characters, which are elementary units of syntax and semantics.
Distance Metric Learning for Aspect Phrase Grouping
Aspect phrase grouping is an important task in aspect-level sentiment analysis.
