Informal Persian Universal Dependency Treebank

Related tags

Deep LearningiPerUDT
Overview

Informal Persian Universal Dependency Treebank (iPerUDT)

Informal Persian Universal Dependency Treebank, consisting of 3000 sentences and 54,904 tokens, is an open source collection of colloquial informal texts from Persian blogs. The corpus is annotated in CoNLL-U format within the Universal Dependencies scheme (Nivre et al., 2020).

The following Course-grained Universal Dependencies parts of speech tags (UPOS), and fine-grained language-specific parts of speech tags (XPOS) are used in this treebank.

UPOS XPOS Description
ADJ ADJ Adjective
ADJ ADJ_CMPR Comparative adjective
ADJ ADJ_SUP Superlative adjective
ADV ADV Adverb
ADV ADV_I Adverb of interrogation
ADV ADV_LOC Adverb of location
ADV ADV_NEG Adverb of Negation
ADV ADV_TIME Adverb of time
ADP P Preposition
AUX V_AUX Auxiliary/copula verb
CCONJ CON Coordinating conjunction
DET DET Determiner
INTJ INTJ Interjection
NOUN N_PL Plural noun
NOUN N_SING Singular noun
NUM NUM Numeral
PART PART Differential object marker, focus marker, negative particle, question particle
PRON PRO Pronoun
PROPN PROPN Proper nouns (persons,locations, months, organizations, geopolitical entities)
PUNCT DELM Punctuation/delimiter
SCONJ CON Subordinating conjunction
VERB V_IMP Imperative verb
VERB V_PA Past tense verb
VERB V_PP Past participle
VERB V_PRS Present tense verb
VERB V_SUB subjunctive verb
X FW Foreign word

We used the Universal Dependencies annotation scheme which produces syntactic analyses of sentences in terms of the dependency structures of dependency grammar, determined by the relation between a head and its dependents. The syntactic annotation consists of 42 dependency relations, including 32 universal and 10 language-specific relations (marked by *).

Dependency relation Description
acl Clausal modifier of noun
acl:relcl* relative clause modifier
advcl Adverbial clause modifier
advmod Adverbial modifier
amod Adjectival modifier
appos Appositional modifier
aux Auxiliary
aux:pass Passive auxiliary
case Accusative marker/case marking
cc Coordination
cc:preconj* Preconjunction
ccomp Clausal complement
compound Compound
compound:lvc* Nominal/adjectival NVE in complex predicates
compound:prt* Particle NVE in complex predicates
compound:redup* Reduplicative words
compound:svc* Serial verb constructions
conj Conjunct
Cop Copula
det Determiner
det:predet* Predeterminer
discourse Discourse element
discourse:top/foc* Topic/focus marker
dislocated Dislocated elements
fixed Fixed multiword expressions
flat Flat multiword expressions
goeswith Goes with for poorly-edited words
nmod Nominal modifier
nmod:poss* Possessive/genitive modifier
nsubj Nominal subject
nsubj:pass Passive nominal subject
nummod Numeric modifier
mark Complementizer/marker
obj Object
obl Oblique
obl:arg* Oblique core argument
orphan Ellipsis constructions
parataxis Parataxis
punct Punctuation
root Root
vocative Vocative
xcomp Open clausal complement

References

Nivre, Joakim, Marie-Catherine de Marneffe, Filip Ginter, Jan Hajič, Christopher D. Manning, Sampo Pyysalo, Sebastian Schuster, Francis M. Tyers, and Dan Zeman. (2020). Universal dependencies v2: An evergrowing multilingual treebank collection. In Proceedings of the 12th Conference on Language Resources and Evaluation (LREC), 4027–4036.

Owner
Roya Kabiri
Computational Linguist
Roya Kabiri
A tool for calculating distortion parameters in coordination complexes.

OctaDist Octahedral distortion calculator: A tool for calculating distortion parameters in coordination complexes. https://octadist.github.io/ Registe

OctaDist 12 Oct 04, 2022
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation

LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh

Payphone 8 Nov 21, 2022
AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

Adelaide Intelligent Machines (AIM) Group 3k Jan 02, 2023
Dynamic Bottleneck for Robust Self-Supervised Exploration

Dynamic Bottleneck Introduction This is a TensorFlow based implementation for our paper on "Dynamic Bottleneck for Robust Self-Supervised Exploration"

Bai Chenjia 4 Nov 14, 2022
Preprocessed Datasets for our Multimodal NER paper

Unified Multimodal Transformer (UMT) for Multimodal Named Entity Recognition (MNER) Two MNER Datasets and Codes for our ACL'2020 paper: Improving Mult

76 Dec 21, 2022
Fast and customizable reconnaissance workflow tool based on simple YAML based DSL.

Fast and customizable reconnaissance workflow tool based on simple YAML based DSL, with support of notifications and distributed workload of that work

Américo Júnior 3 Mar 11, 2022
CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection

CLOCs is a novel Camera-LiDAR Object Candidates fusion network. It provides a low-complexity multi-modal fusion framework that improves the performance of single-modality detectors. CLOCs operates on

Su Pang 254 Dec 16, 2022
Code for "Continuous-Time Meta-Learning with Forward Mode Differentiation" (ICLR 2022)

Continuous-Time Meta-Learning with Forward Mode Differentiation ICLR 2022 (Spotlight) - Installation - Example - Citation This repository contains the

Tristan Deleu 25 Oct 20, 2022
Dynamic Slimmable Network (CVPR 2021, Oral)

Dynamic Slimmable Network (DS-Net) This repository contains PyTorch code of our paper: Dynamic Slimmable Network (CVPR 2021 Oral). Architecture of DS-

Changlin Li 197 Dec 09, 2022
PyTorch implementation of Pay Attention to MLPs

gMLP PyTorch implementation of Pay Attention to MLPs. Quickstart Clone this repository. git clone https://github.com/jaketae/g-mlp.git Navigate to th

Jake Tae 34 Dec 13, 2022
Data cleaning, missing value handle, EDA use in this project

Lending Club Case Study Project Brief Solving this assignment will give you an idea about how real business problems are solved using EDA. In this cas

Dhruvil Sheth 1 Jan 05, 2022
Double pendulum simulator using a symplectic Euler's method and Hamiltonian mechanics

Symplectic Double Pendulum Simulator Double pendulum simulator using a symplectic Euler's method. The program calculates the momentum and position of

Scott Marino 1 Jan 12, 2022
A Fast Monotone Rotating Shallow Water model

pyRSW A Fast Monotone Rotating Shallow Water model How fast? As fast as a sustained 2 Gflop/s per core on a 2.5 GHz cpu (or 2048 Gflop/s with 1024 cor

Guillaume Roullet 13 Sep 28, 2022
SwinIR: Image Restoration Using Swin Transformer

SwinIR: Image Restoration Using Swin Transformer This repository is the official PyTorch implementation of SwinIR: Image Restoration Using Shifted Win

Jingyun Liang 2.4k Jan 08, 2023
ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet, ICCV 2021 Update: 2021/03/11: update our new results. Now our T2T-ViT-14 w

YITUTech 1k Dec 31, 2022
An easy way to build PyTorch datasets. Modularly build datasets and automatically cache processed results

EasyDatas An easy way to build PyTorch datasets. Modularly build datasets and automatically cache processed results Installation pip install git+https

Ximing Yang 4 Dec 14, 2021
Repository for Multimodal AutoML Benchmark

Benchmarking Multimodal AutoML for Tabular Data with Text Fields Repository for the NeurIPS 2021 Dataset Track Submission "Benchmarking Multimodal Aut

Xingjian Shi 44 Nov 24, 2022
A hybrid SOTA solution of LiDAR panoptic segmentation with C++ implementations of point cloud clustering algorithms. ICCV21, Workshop on Traditional Computer Vision in the Age of Deep Learning

ICCVW21-TradiCV-Survey-of-LiDAR-Cluster Motivation In contrast to popular end-to-end deep learning LiDAR panoptic segmentation solutions, we propose a

YimingZhao 103 Nov 22, 2022
ECLARE: Extreme Classification with Label Graph Correlations

ECLARE ECLARE: Extreme Classification with Label Graph Correlations @InProceedings{Mittal21b, author = "Mittal, A. and Sachdeva, N. and Agrawal

Extreme Classification 35 Nov 06, 2022
Minimal But Practical Image Classifier Pipline Using Pytorch, Finetune on ResNet18, Got 99% Accuracy on Own Small Datasets.

PyTorch Image Classifier Updates As for many users request, I released a new version of standared pytorch immage classification example at here: http:

JinTian 106 Nov 06, 2022