TweebankNLP - Pre-trained Tweet NLP Pipeline (NER, tokenization, lemmatization, POS tagging, dependency parsing) + Models + Tweebank-NER

Overview

TweebankNLP

License

This repo contains the new Tweebank-NER dataset and Twitter-Stanza pipeline for state-of-the-art Tweet NLP. Tweebank-NER V1.0 is the annotated NER dataset based on Tweebank V2, the main UD treebank for English Twitter NLP tasks. The Twitter-Stanza pipeline provides pre-trained Tweet NLP models (NER, tokenization, lemmatization, POS tagging, dependency parsing) with state-of-the-art or competitive performance. The models are fully compatible with Stanza and provide both Python and command-line interfaces for users.

Installation

# please install from the source
pip install -e .

# download glove and pre-trained models
sh download_twitter_resources.sh

Python Interface for Twitter-Stanza

import stanza

# config for the `en_tweet` pipeline (trained only on Tweebank)
config = {
          'processors': 'tokenize,lemma,pos,depparse,ner',
          'lang': 'en',
          'tokenize_pretokenized': True, # disable tokenization
          'tokenize_model_path': './saved_models/tokenize/en_tweet_tokenizer.pt',
          'lemma_model_path': './saved_models/lemma/en_tweet_lemmatizer.pt',
          "pos_model_path": './saved_models/pos/en_tweet_tagger.pt',
          "depparse_model_path": './saved_models/depparse/en_tweet_parser.pt',
          "ner_model_path": './saved_models/ner/en_tweet_nertagger.pt'
}

# Initialize the pipeline using a configuration dict
nlp = stanza.Pipeline(**config)
doc = nlp("Oh ikr like Messi better than Ronaldo but we all like Ronaldo more")
print(doc) # Look at the result

Running Twitter-Stanza (Command Line Interface)

NER

We provide two pre-trained Stanza NER models:

  • en_tweenut17: trained on TB2+WNUT17
  • en_tweet: trained on TB2
source twitter-stanza/scripts/config.sh

python stanza/utils/training/run_ner.py en_tweenut17 \
--mode predict \
--score_test \
--wordvec_file ../data/wordvec/English/en.twitter100d.xz \
--eval_file data/ner/en_tweet.test.json

Syntactic NLP Models

We provide two pre-trained models for the following NLP tasks:

  • tweet_ewt: trained on TB2+UD-English-EWT
  • en_tweet: trained on TB2

1. Tokenization

python stanza/utils/training/run_tokenizer.py tweet_ewt \
--mode predict \
--score_test \
--txt_file data/tokenize/en_tweet.test.txt \
--label_file  data/tokenize/en_tweet-ud-test.toklabels \
--no_use_mwt 

2. Lemmatization

python stanza/utils/training/run_lemma.py tweet_ewt \
--mode predict \
--score_test \
--gold_file data/depparse/en_tweet.test.gold.conllu \
--eval_file data/depparse/en_tweet.test.in.conllu 

3. POS Tagging

python stanza/utils/training/run_pos.py tweet_ewt \
--mode predict \
--score_test \
--eval_file data/pos/en_tweet.test.in.conllu \
--gold_file data/depparse/en_tweet.test.gold.conllu 

4. Dependency Parsing

python stanza/utils/training/run_depparse.py tweet_ewt \
--mode predict \
--score_test \
--wordvec_file ../data/wordvec/English/en.twitter100d.txt \
--eval_file data/depparse/en_tweet.test.in.conllu \
--gold_file data/depparse/en_tweet.test.gold.conllu 

Training Twitter-Stanza

Please refer to the TRAIN_README.md for training the Twitter-Stanza neural pipeline.

References

If you use this repository in your research, please kindly cite our paper as well as the Stanza papers.

@article{jiang2022tweebank,
    title={Annotating the Tweebank Corpus on Named Entity Recognition and Building NLP Models for Social Media Analysis},
    author={Jiang, Hang and Hua, Yining and Beeferman, Doug and Roy, Deb},
    publisher={arXiv},
    year={2022}
}

Acknowledgement

The Twitter-Stanza pipeline is a friendly fork from the Stanza libaray with a few modifications to adapt to tweets. The repository is fully compatible with Stanza. This research project is funded by MIT Center for Constructive Communication (CCC).

Owner
Laboratory for Social Machines
Promoting deeper learning and understanding in human networks | Publications: http://socialmachines.org/publications
Laboratory for Social Machines
Pre-training with Extracted Gap-sentences for Abstractive SUmmarization Sequence-to-sequence models

PEGASUS library Pre-training with Extracted Gap-sentences for Abstractive SUmmarization Sequence-to-sequence models, or PEGASUS, uses self-supervised

Google Research 1.4k Dec 22, 2022
Research Code for NeurIPS 2020 Spotlight paper "Large-Scale Adversarial Training for Vision-and-Language Representation Learning": UNITER adversarial training part

VILLA: Vision-and-Language Adversarial Training This is the official repository of VILLA (NeurIPS 2020 Spotlight). This repository currently supports

Zhe Gan 109 Dec 31, 2022
Knowledge Graph,Question Answering System,基于知识图谱和向量检索的医疗诊断问答系统

Knowledge Graph,Question Answering System,基于知识图谱和向量检索的医疗诊断问答系统

wangle 823 Dec 28, 2022
Rethinking the Truly Unsupervised Image-to-Image Translation - Official PyTorch Implementation (ICCV 2021)

Rethinking the Truly Unsupervised Image-to-Image Translation (ICCV 2021) Each image is generated with the source image in the left and the average sty

Clova AI Research 436 Dec 27, 2022
voice2json is a collection of command-line tools for offline speech/intent recognition on Linux

Command-line tools for speech and intent recognition on Linux

Michael Hansen 988 Jan 04, 2023
Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment Analysis with Affective Knowledge. Proceedings of EMNLP 2021

AAGCN-ACSA EMNLP 2021 Introduction This repository was used in our paper: Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment An

Akuchi 36 Dec 18, 2022
TLA - Twitter Linguistic Analysis

TLA - Twitter Linguistic Analysis Tool for linguistic analysis of communities TLA is built using PyTorch, Transformers and several other State-of-the-

Tushar Sarkar 47 Aug 14, 2022
This repository contains the code, data, and models of the paper titled "CrossSum: Beyond English-Centric Cross-Lingual Abstractive Text Summarization for 1500+ Language Pairs".

CrossSum This repository contains the code, data, and models of the paper titled "CrossSum: Beyond English-Centric Cross-Lingual Abstractive Text Summ

BUET CSE NLP Group 29 Nov 19, 2022
Text to speech converter with GUI made in Python.

Text-to-speech-with-GUI Text to speech converter with GUI made in Python. To run this download the zip file and run the main file or clone this repo.

SidTheMiner 1 Nov 15, 2021
Convolutional Neural Networks for Sentence Classification

Convolutional Neural Networks for Sentence Classification Code for the paper Convolutional Neural Networks for Sentence Classification (EMNLP 2014). R

Yoon Kim 2k Jan 02, 2023
🤕 spelling exceptions builder for lazy people

🤕 spelling exceptions builder for lazy people

Vlad Bokov 3 May 12, 2022
Code for our paper "Transfer Learning for Sequence Generation: from Single-source to Multi-source" in ACL 2021.

TRICE: a task-agnostic transferring framework for multi-source sequence generation This is the source code of our work Transfer Learning for Sequence

THUNLP-MT 9 Jun 27, 2022
An implementation of WaveNet with fast generation

pytorch-wavenet This is an implementation of the WaveNet architecture, as described in the original paper. Features Automatic creation of a dataset (t

Vincent Herrmann 858 Dec 27, 2022
Finds snippets in iambic pentameter in English-language text and tries to combine them to a rhyming sonnet.

Sonnet finder Finds snippets in iambic pentameter in English-language text and tries to combine them to a rhyming sonnet. Usage This is a Python scrip

Marcel Bollmann 11 Sep 25, 2022
ReCoin - Restoring our environment and businesses in parallel

Shashank Ojha, Sabrina Button, Abdellah Ghassel, Joshua Gonzales "Reduce Reuse R

sabrina button 1 Mar 14, 2022
Pretrain CPM - 大规模预训练语言模型的预训练代码

CPM-Pretrain 版本更新记录 为了促进中文自然语言处理研究的发展,本项目提供了大规模预训练语言模型的预训练代码。项目主要基于DeepSpeed、Megatron实现,可以支持数据并行、模型加速、流水并行的代码。 安装 1、首先安装pytorch等基础依赖,再安装APEX以支持fp16。 p

Tsinghua AI 37 Dec 06, 2022
Top2Vec is an algorithm for topic modeling and semantic search.

Top2Vec is an algorithm for topic modeling and semantic search. It automatically detects topics present in text and generates jointly embedded topic, document and word vectors.

Dimo Angelov 2.4k Jan 06, 2023
Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external libs usage.

TextDistance TextDistance -- python library for comparing distance between two or more sequences by many algorithms. Features: 30+ algorithms Pure pyt

Life4 3k Jan 06, 2023
A script that automatically creates a branch name using google translation api and jira api

About google translation api와 jira api을 사용하여 자동으로 브랜치 이름을 만들어주는 스크립트 Setup 환경변수에 다음 3가지를 등록해야 한다. JIRA_USER : JIRA email (ex: hyunwook.kim 2 Dec 20, 2021

Prithivida 690 Jan 04, 2023