Semantic Role Labeling

132 papers with code • 7 benchmarks • 14 datasets

Semantic role labeling aims to model the predicate-argument structure of a sentence and is often described as answering "Who did what to whom". BIO notation is typically used for semantic role labeling.

Example:

Housing starts are expected to quicken a bit from August’s pace
B-ARG1 I-ARG1 O O O V B-ARG2 I-ARG2 B-ARG3 I-ARG3 I-ARG3

Most implemented papers

A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling

diegma/neural-dep-srl CONLL 2017

However, when automatically predicted part-of-speech tags are provided as input, it substantially outperforms all previous local models and approaches the best reported results on the English CoNLL-2009 dataset.

Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling

diegma/neural-dep-srl EMNLP 2017

GCNs over syntactic dependency trees are used as sentence encoders, producing latent feature representations of words in a sentence.

Glyce: Glyph-vectors for Chinese Character Representations

ShannonAI/glyce NeurIPS 2019

However, due to the lack of rich pictographic evidence in glyphs and the weak generalization ability of standard computer vision models on character data, an effective way to utilize the glyph information remains to be found.

BERTje: A Dutch BERT Model

wietsedv/bertje 19 Dec 2019

The transformer-based pre-trained language model BERT has helped to improve state-of-the-art performance on many natural language processing (NLP) tasks.

ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs

chenllliang/atp Findings (NAACL) 2022

As Abstract Meaning Representation (AMR) implicitly involves compound semantic annotations, we hypothesize auxiliary tasks which are semantically or formally related can better enhance AMR parsing.

Speaker attribution in German parliamentary debates with QLoRA-adapted large language models

dslaborg/germeval2023 18 Sep 2023

The growing body of political texts opens up new opportunities for rich insights into political dynamics and ideologies but also increases the workload for manual analysis.

Context-aware Frame-Semantic Role Labeling

microth/mateplus TACL 2015

Frame semantic representations have been useful in several applications ranging from text-to-scene generation, to question answering and social network analysis.

Visual Semantic Role Labeling

s-gupta/v-coco 17 May 2015

In this paper we introduce the problem of Visual Semantic Role Labeling: given an image we want to detect people doing actions and localize the objects of interaction.