Search Results for author: Johannes Deleu

Found 17 papers, 9 papers with code

Towards Consistent Document-level Entity Linking: Joint Models for Entity Linking and Coreference Resolution

no code implementations30 Aug 2021 Klim Zaporojets, Johannes Deleu, Thomas Demeester, Chris Develder

We consider the task of document-level entity linking (EL), where it is important to make consistent decisions for entity mentions over the full document jointly.

Coreference Resolution Document-level +2

Injecting Knowledge Base Information into End-to-End Joint Entity and Relation Extraction and Coreference Resolution

1 code implementation5 Jul 2021 Severine Verlinden, Klim Zaporojets, Johannes Deleu, Thomas Demeester, Chris Develder

The used KB entity representations are learned from either (i) hyperlinked text documents (Wikipedia), or (ii) a knowledge graph (Wikidata), and appear complementary in raising IE performance.

Coreference Resolution Entity Linking +2

DWIE: an entity-centric dataset for multi-task document-level information extraction

1 code implementation26 Sep 2020 Klim Zaporojets, Johannes Deleu, Chris Develder, Thomas Demeester

Second, the document-level multi-task annotations require the models to transfer information between entity mentions located in different parts of the document, as well as between different tasks, in a joint learning setting.

 Ranked #1 on Coreference Resolution on DWIE (Avg. F1 metric)

Coreference Resolution Document-level +5

Solving Arithmetic Word Problems by Scoring Equations with Recursive Neural Networks

no code implementations11 Sep 2020 Klim Zaporojets, Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder

Recent works use automatic extraction and ranking of candidate solution equations providing the answer to arithmetic word problems.

Block-wise Dynamic Sparseness

1 code implementation14 Jan 2020 Amir Hadifar, Johannes Deleu, Chris Develder, Thomas Demeester

In this paper, we present a new method for \emph{dynamic sparseness}, whereby part of the computations are omitted dynamically, based on the input.

Language Modelling

Sub-event detection from Twitter streams as a sequence labeling problem

1 code implementation NAACL 2019 Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder

This paper introduces improved methods for sub-event detection in social media streams, by applying neural sequence models not only on the level of individual posts, but also directly on the stream level.

Event Detection

Definition and evaluation of model-free coordination of electrical vehicle charging with reinforcement learning

no code implementations27 Sep 2018 Nasrin Sadeghianpourhamami, Johannes Deleu, Chris Develder

In this paper, we propose a new Markov decision process (MDP) formulation in the RL framework, to jointly coordinate a set of EV charging stations.

Predefined Sparseness in Recurrent Sequence Models

1 code implementation CONLL 2018 Thomas Demeester, Johannes Deleu, Fréderic Godin, Chris Develder

Inducing sparseness while training neural networks has been shown to yield models with a lower memory footprint but similar effectiveness to dense models.

Language Modelling Word Embeddings

Adversarial training for multi-context joint entity and relation extraction

1 code implementation EMNLP 2018 Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder

Adversarial training (AT) is a regularization method that can be used to improve the robustness of neural network methods by adding small perturbations in the training data.

Joint Entity and Relation Extraction

Prior Attention for Style-aware Sequence-to-Sequence Models

no code implementations25 Jun 2018 Lucas Sterckx, Johannes Deleu, Chris Develder, Thomas Demeester

We extend sequence-to-sequence models with the possibility to control the characteristics or style of the generated output, via attention that is generated a priori (before decoding) from a latent code vector.

Lexical Simplification

Joint entity recognition and relation extraction as a multi-head selection problem

6 code implementations20 Apr 2018 Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder

State-of-the-art models for joint entity recognition and relation extraction strongly rely on external natural language processing (NLP) tools such as POS (part-of-speech) taggers and dependency parsers.

POS

An attentive neural architecture for joint segmentation and parsing and its application to real estate ads

1 code implementation27 Sep 2017 Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder

In this work, we propose a new joint model that is able to tackle the two tasks simultaneously and construct the property tree by (i) avoiding the error propagation that would arise from the subtasks one after the other in a pipelined fashion, and (ii) exploiting the interactions between the subtasks.

Dependency Parsing

Reconstructing the house from the ad: Structured prediction on real estate classifieds

1 code implementation EACL 2017 Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder

In this paper, we address the (to the best of our knowledge) new problem of extracting a structured description of real estate properties from their natural language descriptions in classifieds.

Dependency Parsing Named Entity Recognition +1

Knowledge Base Population using Semantic Label Propagation

no code implementations19 Nov 2015 Lucas Sterckx, Thomas Demeester, Johannes Deleu, Chris Develder

We propose to combine distant supervision with minimal manual supervision in a technique called feature labeling, to eliminate noise from the large and noisy initial training set, resulting in a significant increase of precision.

Knowledge Base Population

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