From 0868ef694e978830a4fc7edb43075618247fcb66 Mon Sep 17 00:00:00 2001
From: dano <dhladek@gmail.com>
Date: Fri, 3 Sep 2021 06:52:26 +0000
Subject: [PATCH] Update 'pages/topics/question/README.md'

---
 pages/topics/question/README.md | 102 ++++++++++++++++++--------------
 1 file changed, 58 insertions(+), 44 deletions(-)

diff --git a/pages/topics/question/README.md b/pages/topics/question/README.md
index 024d798a6..edcccc146 100644
--- a/pages/topics/question/README.md
+++ b/pages/topics/question/README.md
@@ -11,6 +11,7 @@ taxonomy:
 - [Project repository](https://git.kemt.fei.tuke.sk/dano/annotation) (private)
 - [Annotation Manual for question annotation](navod)
 - [Annotation Manual for validations](validacie)
+- [Annotation Manual for unanswerable questions](nezodpovedatelne)
 - [Summary database application](https://app.question.tukekemt,xyz)
 
 
@@ -63,6 +64,19 @@ Notes:
 - [167 good articles](https://sk.wikipedia.org/wiki/Wikip%C3%A9dia:Zoznam_dobr%C3%BDch_%C4%8Dl%C3%A1nkov)
 - [Wiki Facts](https://sk.wikipedia.org/wiki/Wikip%C3%A9dia:Zauj%C3%ADmavosti)
 
+## Finished Tasks
+
+### Annotation Manual
+
+Output: Recommendations for annotators
+
+Done:
+
+- Web Page for annotators  (Daniel Hládek)
+- Modivation video (Daniel Hládek)
+- Video with instructions (Daniel Hládek)
+bn application?
+
 ### Question Annotation
 
 An annotation recipe for Prodigy
@@ -79,15 +93,6 @@ Done:
 - answer annotation together with question (Daniel Hládek)
 - prepare final input paragraphs (dataset)
 
-In progress:
-
-- More annotations (volunteers and workers).
-
-To be done:
-
-- Prepare development set 
-
-
 ### Annotation Web Application
 
 Annotation work summary, web applicatiobn
@@ -104,11 +109,6 @@ Done:
 - application deployment (Daniel Hládek)
 - extract annotations from question annotation in squad format (Daniel Hladek)
 
-
-To be done:
-
-- review of validations
-
 ### Annotation Validation
 
 Input: annnotated questions and paragraph
@@ -120,60 +120,53 @@ Done:
 - Recipe for validations (binary annotation for paragraphs, question and answers, text fields for correction of question and answer). (Daniel Hládek)
 - Deployment 
 
-To be done:
 
-- Prepare for production
+## Tasks in progress
 
-### Annotation Manual
+### Unanswerable question annotation
 
-Output: Recommendations for annotators
+Input: validated questions and answers
+
+Output: Unanswerable questions and answers
 
 Done:
 
-- Web Page for annotators  (Daniel Hládek)
-- Modivation video (Daniel Hládek)
-- Video with instructions (Daniel Hládek)
+- Annotation manual
+- Annotation interface
+- Database schema modifications
+- Modification of the database application
+- Export of validations
 
 In progress:
 
-- Should be instructions a part of the annotation webn application?
+- Annotaion process optimization
 
-### Question Answering Model
+### Final Data Export
 
-Training the model with annotated data
+Input: Validations and unanswerable questions
 
-Input: An annotated QA database
+Output: Final database in SQUAD format
 
-Output: An evaluated model for QA
+Done:
+
+- Preliminary export script
 
 To be done:
 
-- Selecting existing modelling approach
-- Evaluation set selection
-- Model evaluation
-- Supporting the annotation with the model (pre-selecting answers)
+- Final export script
+- Database web visualization
+- Prepare development set 
 
-In progress:
+## Resources
 
-- Preliminary model (Ján Staš and Matej Čarňanský)
-
-
-
-## Existing implementations
-
-- https://github.com/facebookresearch/DrQA
-- https://github.com/brmson/yodaqa
-- https://github.com/5hirish/adam_qas
-- https://github.com/WDAqua/Qanary - metodológia a implementácia QA
-
-## Bibligraphy
+### Bibligraphy
 
 - Reading Wikipedia to Answer Open-Domain Questions, Danqi Chen, Adam Fisch, Jason Weston, Antoine Bordes
 Facebook Research
 - SQuAD: 100,000+ Questions for Machine Comprehension of Text https://arxiv.org/abs/1606.05250
 - [WDaqua](https://wdaqua.eu/our-work/) publications
 
-## Existing Datasets
+### Existing Datasets
 
 - [Squad](https://rajpurkar.github.io/SQuAD-explorer/)  The Stanford Question Answering Dataset(SQuAD)  (Rajpurkar  et  al.,  2016) 
 - [WebQuestions](https://github.com/brmson/dataset-factoid-webquestions)
@@ -210,3 +203,24 @@ Output:
 - a trained model
 - evaluation of the model (if possible)
 
+
+### Question Answering Model
+
+Training the model with annotated data
+
+Input: An annotated QA database
+
+Output: An evaluated model for QA
+
+To be done:
+
+- Selecting existing modelling approach
+- Evaluation set selection
+- Model evaluation
+- Supporting the annotation with the model (pre-selecting answers)
+
+In progress:
+
+- Preliminary model (Ján Staš and Matej Čarňanský)
+
+