This repository contains (not all) code from my project on Named Entity Recognition in philosophical text

Related tags

Text Data & NLPNERphilosophy
Overview

NERphilosophy

👋 Welcome to the github repository of my BsC thesis.

This repository contains (not all) code from my project on Named Entity Recognition in philosophical text.

✔️ In this repository you will find code on:

  • Cleaning & preprocessing data
  • Rule-based, SpaCy and FLAIR models
  • The Merged corpus (and its creation)

📁 I coded in many different files, and the code was a little all over the place at times. Some steps I took are not to be found in the selection of files I uploaded.

📧 If anything is unclear, or if you have questions about the code, steps I took, or the project, please feel free to email me at [email protected] and I will try to answer your questions.

❎ The FLAIR models are not included since they are over 100MB. The gold standard is also not included since it is private data.

📬 To request access to one of these, send me an email and I will discuss it with my supervisor (Dr. J. Bloem).

Owner
Ruben
BsC in AI from the University of Amsterdam Starting the MsC Human Computer Interaction at Utrecht University in Februari 2022
Ruben
GitHub Repository
The aim of this task is to predict someone's English proficiency based on a text input.

English_proficiency_prediction_NLP The aim of this task is to predict someone's English proficiency based on a text input. Using the The NICT JLE Corp

1 Dec 13, 2021
LUKE -- Language Understanding with Knowledge-based Embeddings

LUKE (Language Understanding with Knowledge-based Embeddings) is a new pre-trained contextualized representation of words and entities based on transf

Studio Ousia 587 Dec 30, 2022
Sinkhorn Transformer - Practical implementation of Sparse Sinkhorn Attention

Sinkhorn Transformer This is a reproduction of the work outlined in Sparse Sinkhorn Attention, with additional enhancements. It includes a parameteriz

Phil Wang 217 Nov 25, 2022
An easy-to-use framework for BERT models, with trainers, various NLP tasks and detailed annonations

FantasyBert English | 中文 Introduction An easy-to-use framework for BERT models, with trainers, various NLP tasks and detailed annonations. You can imp

Fan 137 Oct 26, 2022
Non-Autoregressive Translation with Layer-Wise Prediction and Deep Supervision

Deeply Supervised, Layer-wise Prediction-aware (DSLP) Transformer for Non-autoregressive Neural Machine Translation

Chenyang Huang 37 Jan 04, 2023
A look-ahead multi-entity Transformer for modeling coordinated agents.

baller2vec++ This is the repository for the paper: Michael A. Alcorn and Anh Nguyen. baller2vec++: A Look-Ahead Multi-Entity Transformer For Modeling

Michael A. Alcorn 30 Dec 16, 2022
🕹 An esoteric language designed so that the program looks like the transcript of a Pokémon battle

PokéBattle is an esoteric language designed so that the program looks like the transcript of a Pokémon battle. Original inspiration and specification

Eduardo Correia 9 Jan 11, 2022
Implementation of TTS with combination of Tacotron2 and HiFi-GAN

Tacotron2-HiFiGAN-master Implementation of TTS with combination of Tacotron2 and HiFi-GAN for Mandarin TTS. Inference In order to inference, we need t

SunLu Z 7 Nov 11, 2022
Python SDK for working with Voicegain Speech-to-Text

Voicegain Speech-to-Text Python SDK Python SDK for the Voicegain Speech-to-Text API. This API allows for large vocabulary speech-to-text transcription

Voicegain 3 Dec 14, 2022
HAN2HAN : Hangul Font Generation

HAN2HAN : Hangul Font Generation

Changwoo Lee 36 Dec 28, 2022
💫 Industrial-strength Natural Language Processing (NLP) in Python

spaCy: Industrial-strength NLP spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest researc

Explosion 24.9k Jan 02, 2023
The training code for the 4th place model at MDX 2021 leaderboard A.

The training code for the 4th place model at MDX 2021 leaderboard A.

Chin-Yun Yu 32 Dec 18, 2022
FedNLP: A Benchmarking Framework for Federated Learning in Natural Language Processing

FedNLP is a research-oriented benchmarking framework for advancing federated learning (FL) in natural language processing (NLP). It uses FedML repository as the git submodule. In other words, FedNLP

FedML-AI 216 Nov 27, 2022
A single model that parses Universal Dependencies across 75 languages.

A single model that parses Universal Dependencies across 75 languages. Given a sentence, jointly predicts part-of-speech tags, morphology tags, lemmas, and dependency trees.

Dan Kondratyuk 189 Nov 29, 2022
In this repository we have tested 3 VQA models on the ImageCLEF-2019 dataset.

Med-VQA In this repository we have tested 3 VQA models on the ImageCLEF-2019 dataset. Two of these are made on top of Facebook AI Reasearch's Multi-Mo

Kshitij Ambilduke 8 Apr 14, 2022
Using Bert as the backbone model for lime, designed for NLP task explanation (sentence pair text classification task)

Lime Comparing deep contextualized model for sentences highlighting task. In addition, take the classic explanation model "LIME" with bert-base model

JHJu 2 Jan 18, 2022
Modeling cumulative cases of Covid-19 in the US during the Covid 19 Delta wave using Bayesian methods.

Introduction The goal of this analysis is to find a model that fits the observed cumulative cases of COVID-19 in the US, starting in Mid-July 2021 and

Alexander Keeney 1 Jan 05, 2022
Continuously update some NLP practice based on different tasks.

NLP_practice We will continuously update some NLP practice based on different tasks. prerequisites Software pytorch = 1.10 torchtext = 0.11.0 sklear

0 Jan 05, 2022
Prompt tuning toolkit for GPT-2 and GPT-Neo

mkultra mkultra is a prompt tuning toolkit for GPT-2 and GPT-Neo. Prompt tuning injects a string of 20-100 special tokens into the context in order to

61 Jan 01, 2023
Using context-free grammar formalism to parse English sentences to determine their structure to help computer to better understand the meaning of the sentence.

Sentance Parser Executing the Program Make sure Python 3.6+ is installed. Install requirements $ pip install requirements.txt Run the program:

Vaibhaw 12 Sep 28, 2022