docs: preserve upstream English README
This commit is contained in:
wehub-resource-sync
+212
@@ -0,0 +1,212 @@
|
||||
# Tracking Progress in Natural Language Processing
|
||||
|
||||
## Table of contents
|
||||
|
||||
### English
|
||||
|
||||
- [Automatic speech recognition](english/automatic_speech_recognition.md)
|
||||
- [CCG](english/ccg.md)
|
||||
- [Common sense](english/common_sense.md)
|
||||
- [Constituency parsing](english/constituency_parsing.md)
|
||||
- [Coreference resolution](english/coreference_resolution.md)
|
||||
- [Data-to-Text Generation](english/data_to_text_generation.md)
|
||||
- [Dependency parsing](english/dependency_parsing.md)
|
||||
- [Dialogue](english/dialogue.md)
|
||||
- [Domain adaptation](english/domain_adaptation.md)
|
||||
- [Entity linking](english/entity_linking.md)
|
||||
- [Grammatical error correction](english/grammatical_error_correction.md)
|
||||
- [Information extraction](english/information_extraction.md)
|
||||
- [Intent Detection and Slot Filling](english/intent_detection_slot_filling.md)
|
||||
- [Keyphrase Extraction and Generation](english/keyphrase_extraction_generation.md)
|
||||
- [Language modeling](english/language_modeling.md)
|
||||
- [Lexical normalization](english/lexical_normalization.md)
|
||||
- [Machine translation](english/machine_translation.md)
|
||||
- [Missing elements](english/missing_elements.md)
|
||||
- [Multi-task learning](english/multi-task_learning.md)
|
||||
- [Multi-modal](english/multimodal.md)
|
||||
- [Named entity recognition](english/named_entity_recognition.md)
|
||||
- [Natural language inference](english/natural_language_inference.md)
|
||||
- [Part-of-speech tagging](english/part-of-speech_tagging.md)
|
||||
- [Paraphrase Generation](english/paraphrase-generation.md)
|
||||
- [Question answering](english/question_answering.md)
|
||||
- [Relation prediction](english/relation_prediction.md)
|
||||
- [Relationship extraction](english/relationship_extraction.md)
|
||||
- [Semantic textual similarity](english/semantic_textual_similarity.md)
|
||||
- [Semantic parsing](english/semantic_parsing.md)
|
||||
- [Semantic role labeling](english/semantic_role_labeling.md)
|
||||
- [Sentiment analysis](english/sentiment_analysis.md)
|
||||
- [Shallow syntax](english/shallow_syntax.md)
|
||||
- [Simplification](english/simplification.md)
|
||||
- [Stance detection](english/stance_detection.md)
|
||||
- [Summarization](english/summarization.md)
|
||||
- [Taxonomy learning](english/taxonomy_learning.md)
|
||||
- [Temporal processing](english/temporal_processing.md)
|
||||
- [Text classification](english/text_classification.md)
|
||||
- [Word sense disambiguation](english/word_sense_disambiguation.md)
|
||||
|
||||
### Vietnamese
|
||||
|
||||
- [Dependency parsing](vietnamese/vietnamese.md#dependency-parsing)
|
||||
- [Intent detection and Slot filling](vietnamese/vietnamese.md#intent-detection-and-slot-filling)
|
||||
- [Machine translation](vietnamese/vietnamese.md#machine-translation)
|
||||
- [Named entity recognition](vietnamese/vietnamese.md#named-entity-recognition)
|
||||
- [Part-of-speech tagging](vietnamese/vietnamese.md#part-of-speech-tagging)
|
||||
- [Semantic parsing](vietnamese/vietnamese.md#semantic-parsing)
|
||||
- [Word segmentation](vietnamese/vietnamese.md#word-segmentation)
|
||||
|
||||
### Hindi
|
||||
|
||||
- [Chunking](hindi/hindi.md#chunking)
|
||||
- [Part-of-speech tagging](hindi/hindi.md#part-of-speech-tagging)
|
||||
- [Machine Translation](hindi/hindi.md#machine-translation)
|
||||
|
||||
### Chinese
|
||||
|
||||
- [Entity linking](chinese/chinese.md#entity-linking)
|
||||
- [Chinese word segmentation](chinese/chinese_word_segmentation.md)
|
||||
- [Question answering](chinese/question_answering.md)
|
||||
|
||||
For more tasks, datasets and results in Chinese, check out the [Chinese NLP](https://chinesenlp.xyz/#/) website.
|
||||
|
||||
### French
|
||||
|
||||
- [Question answering](french/question_answering.md)
|
||||
- [Summarization](french/summarization.md)
|
||||
|
||||
### Russian
|
||||
|
||||
- [Question answering](russian/question_answering.md)
|
||||
- [Sentiment Analysis](russian/sentiment-analysis.md)
|
||||
- [Summarization](russian/summarization.md)
|
||||
|
||||
### Spanish
|
||||
|
||||
- [Named Entity Recognition](spanish/named_entity_recognition.md)
|
||||
- [Entity linking](spanish/entity_linking.md#entity-linking)
|
||||
- [Summarization](spanish/summarization.md)
|
||||
|
||||
### Portuguese
|
||||
|
||||
- [Question Answering](portuguese/question_answering.md)
|
||||
|
||||
### Korean
|
||||
|
||||
- [Question Answering](korean/question_answering.md)
|
||||
|
||||
### Nepali
|
||||
|
||||
- [Machine Translation](nepali/nepali.md#machine-translation)
|
||||
|
||||
### Bengali
|
||||
- [Part-of-speech Tagging](bengali/part_of_speech_tagging.md)
|
||||
- [Emotion Detection](bengali/emotion_detection.md)
|
||||
- [Sentiment Analysis](bengali/sentiment_analysis.md)
|
||||
|
||||
### Persian
|
||||
- [Named entity recognition](persian/named_entity_recognition.md)
|
||||
- [Natural language inference](persian/natural_language_inference.md)
|
||||
- [Summarization](persian/summarization.md)
|
||||
|
||||
### Turkish
|
||||
|
||||
- [Summarization](turkish/summarization.md)
|
||||
|
||||
### German
|
||||
|
||||
- [Question Answering](german/question_answering.md)
|
||||
- [Summarization](german/summarization.md)
|
||||
|
||||
### Arabic
|
||||
- [Language modeling](arabic/language_modeling.md)
|
||||
|
||||
|
||||
This document aims to track the progress in Natural Language Processing (NLP) and give an overview
|
||||
of the state-of-the-art (SOTA) across the most common NLP tasks and their corresponding datasets.
|
||||
|
||||
It aims to cover both traditional and core NLP tasks such as dependency parsing and part-of-speech tagging
|
||||
as well as more recent ones such as reading comprehension and natural language inference. The main objective
|
||||
is to provide the reader with a quick overview of benchmark datasets and the state-of-the-art for their
|
||||
task of interest, which serves as a stepping stone for further research. To this end, if there is a
|
||||
place where results for a task are already published and regularly maintained, such as a public leaderboard,
|
||||
the reader will be pointed there.
|
||||
|
||||
If you want to find this document again in the future, just go to [`nlpprogress.com`](https://nlpprogress.com/)
|
||||
or [`nlpsota.com`](http://nlpsota.com/) in your browser.
|
||||
|
||||
### Contributing
|
||||
|
||||
#### Guidelines
|
||||
|
||||
**Results** Results reported in published papers are preferred; an exception may be made for influential preprints.
|
||||
|
||||
**Datasets** Datasets should have been used for evaluation in at least one published paper besides
|
||||
the one that introduced the dataset.
|
||||
|
||||
**Code** We recommend to add a link to an implementation
|
||||
if available. You can add a `Code` column (see below) to the table if it does not exist.
|
||||
In the `Code` column, indicate an official implementation with [Official](http://link_to_implementation).
|
||||
If an unofficial implementation is available, use [Link](http://link_to_implementation) (see below).
|
||||
If no implementation is available, you can leave the cell empty.
|
||||
|
||||
#### Adding a new result
|
||||
|
||||
If you would like to add a new result, you can just click on the small edit button in the top-right
|
||||
corner of the file for the respective task (see below).
|
||||
|
||||
|
||||
|
||||
This allows you to edit the file in Markdown. Simply add a row to the corresponding table in the
|
||||
same format. Make sure that the table stays sorted (with the best result on top).
|
||||
After you've made your change, make sure that the table still looks ok by clicking on the
|
||||
"Preview changes" tab at the top of the page. If everything looks good, go to the bottom of the page,
|
||||
where you see the below form.
|
||||
|
||||
|
||||
|
||||
Add a name for your proposed change, an optional description, indicate that you would like to
|
||||
"Create a new branch for this commit and start a pull request", and click on "Propose file change".
|
||||
|
||||
#### Adding a new dataset or task
|
||||
|
||||
For adding a new dataset or task, you can also follow the steps above. Alternatively, you can fork the repository.
|
||||
In both cases, follow the steps below:
|
||||
|
||||
1. If your task is completely new, create a new file and link to it in the table of contents above.
|
||||
2. If not, add your task or dataset to the respective section of the corresponding file (in alphabetical order).
|
||||
3. Briefly describe the dataset/task and include relevant references.
|
||||
4. Describe the evaluation setting and evaluation metric.
|
||||
5. Show how an annotated example of the dataset/task looks like.
|
||||
6. Add a download link if available.
|
||||
7. Copy the below table and fill in at least two results (including the state-of-the-art)
|
||||
for your dataset/task (change Score to the metric of your dataset). If your dataset/task
|
||||
has multiple metrics, add them to the right of `Score`.
|
||||
1. Submit your change as a pull request.
|
||||
|
||||
| Model | Score | Paper / Source | Code |
|
||||
| ------------- | :-----:| --- | --- |
|
||||
| | | | |
|
||||
|
||||
|
||||
### Wish list
|
||||
|
||||
These are tasks and datasets that are still missing:
|
||||
|
||||
- Bilingual dictionary induction
|
||||
- Discourse parsing
|
||||
- Keyphrase extraction
|
||||
- Knowledge base population (KBP)
|
||||
- More dialogue tasks
|
||||
- Semi-supervised learning
|
||||
- Frame-semantic parsing (FrameNet full-sentence analysis)
|
||||
|
||||
### Exporting into a structured format
|
||||
|
||||
You can extract all the data into a structured, machine-readable JSON format with parsed tasks, descriptions and SOTA tables.
|
||||
|
||||
The instructions are in [structured/README.md](structured/README.md).
|
||||
|
||||
### Instructions for building the site locally
|
||||
|
||||
Instructions for building the website locally using Jekyll can be found [here](jekyll_instructions.md).
|
||||
|
||||
|
||||
Reference in New Issue
Block a user