From 17a9338d9fa64c4c45f74fc6d8d49e441ae63473 Mon Sep 17 00:00:00 2001 From: Patrick Jentsch Date: Wed, 29 Nov 2023 16:11:14 +0100 Subject: [PATCH 1/4] Fix job deletion from job page --- app/templates/jobs/job.html.j2 | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/app/templates/jobs/job.html.j2 b/app/templates/jobs/job.html.j2 index 7fad7bcb..f6d71719 100644 --- a/app/templates/jobs/job.html.j2 +++ b/app/templates/jobs/job.html.j2 @@ -153,16 +153,16 @@ let deleteJobRequestElement = document.querySelector('#delete-job-request'); let restartJobRequestElement = document.querySelector('#restart-job-request'); deleteJobRequestElement.addEventListener('click', (event) => { - requests.jobs.entity.delete({{ job.hashid|tojson }}); + nopaque.requests.jobs.entity.delete({{ job.hashid|tojson }}); }); restartJobRequestElement.addEventListener('click', (event) => { - requests.jobs.entity.restart({{ job.hashid|tojson }}); + nopaque.requests.jobs.entity.restart({{ job.hashid|tojson }}); }); if ({{ current_user.is_administrator()|tojson }}) { let jobLogButtonElement = document.querySelector('#job-log-button'); jobLogButtonElement.addEventListener('click', (event) => { - requests.jobs.entity.log({{ job.hashid|tojson }}) + nopaque.requests.jobs.entity.log({{ job.hashid|tojson }}) .then( (response) => { response.json() From 678a0767b7e0ce4561b777533a04eef01aaa10c6 Mon Sep 17 00:00:00 2001 From: Patrick Jentsch Date: Thu, 30 Nov 2023 11:21:39 +0100 Subject: [PATCH 2/4] Change Manual icon --- app/templates/_base/navbar.html.j2 | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/app/templates/_base/navbar.html.j2 b/app/templates/_base/navbar.html.j2 index 1242e310..aab85321 100644 --- a/app/templates/_base/navbar.html.j2 +++ b/app/templates/_base/navbar.html.j2 @@ -30,7 +30,7 @@ {% endif %} {%- endfor -%} - help + school From c57acc73d2ec616b9352a46c9928195fabbe7b6c Mon Sep 17 00:00:00 2001 From: Gloria Glinphratum Date: Tue, 5 Dec 2023 14:42:38 +0100 Subject: [PATCH 3/4] Manual changes --- .../_modals/_manual/03_dashboard.html.j2 | 8 +++--- .../_base/_modals/_manual/06_services.html.j2 | 6 ++--- ...closer_look_at_the_corpus_analysis.html.j2 | 4 +-- .../_modals/_manual/09_query_builder.html.j2 | 26 +++++++++++++------ 4 files changed, 27 insertions(+), 17 deletions(-) diff --git a/app/templates/_base/_modals/_manual/03_dashboard.html.j2 b/app/templates/_base/_modals/_manual/03_dashboard.html.j2 index e62fd434..51d772a3 100644 --- a/app/templates/_base/_modals/_manual/03_dashboard.html.j2 +++ b/app/templates/_base/_modals/_manual/03_dashboard.html.j2 @@ -8,7 +8,7 @@ The dashboard provides a central overview of all resources assigned to the user. These are corpora and created jobs. Corpora are freely composable annotated text collections and jobs are the initiated file processing - procedures. Both the job and the corpus listings can be searched using + procedures. One can search for jobs as well as corpus listings using the search field displayed above them.

@@ -20,10 +20,10 @@

A corpus is a collection of texts that can be analyzed using the Corpus Analysis service. All texts must be in the verticalized text - file format, which can be obtained via the Natrual Language - Processing service. It contains, in addition to the actual text, + file format, which can be obtained via the Natural Language + Processing service. It contains, in addition to the text, further annotations that are searchable in combination with optional - addable metadata during your analysis. + metadata that can be added during your analysis.

diff --git a/app/templates/_base/_modals/_manual/06_services.html.j2 b/app/templates/_base/_modals/_manual/06_services.html.j2 index fcb986e3..e65f8088 100644 --- a/app/templates/_base/_modals/_manual/06_services.html.j2 +++ b/app/templates/_base/_modals/_manual/06_services.html.j2 @@ -35,13 +35,13 @@

Optical Character Recognition (OCR)

-

Comming soon...

+

Coming soon...

Handwritten Text Recognition (HTR)

-

Comming soon...

+

Coming soon...

Natural Language Processing (NLP)

-

Comming soon...

+

Coming soon...

Corpus Analysis

diff --git a/app/templates/_base/_modals/_manual/07_a_closer_look_at_the_corpus_analysis.html.j2 b/app/templates/_base/_modals/_manual/07_a_closer_look_at_the_corpus_analysis.html.j2 index b2a500c8..db9b6e5f 100644 --- a/app/templates/_base/_modals/_manual/07_a_closer_look_at_the_corpus_analysis.html.j2 +++ b/app/templates/_base/_modals/_manual/07_a_closer_look_at_the_corpus_analysis.html.j2 @@ -7,7 +7,7 @@

To create a corpus, you - can use the "New Corpus" button, which can be found on both, the Corpus + can use the "New Corpus" button, which can be found on both the Corpus Analysis Service page and the Dashboard below the corpus list. Fill in the input mask to Create a corpus. After you have completed the input mask, you will be automatically taken to the corpus overview page (which can be called up @@ -43,5 +43,5 @@ the way of how a token is displayed, by using the text style switch. The concordance module offers some more options regarding the context size of search results. If the context does not provide enough information you can - hop into the reader module by using the lupe icon next to a match. + hop into the reader module by using the magnifier icon next to a match.

diff --git a/app/templates/_base/_modals/_manual/09_query_builder.html.j2 b/app/templates/_base/_modals/_manual/09_query_builder.html.j2 index ea1a07a7..be36748c 100644 --- a/app/templates/_base/_modals/_manual/09_query_builder.html.j2 +++ b/app/templates/_base/_modals/_manual/09_query_builder.html.j2 @@ -1,14 +1,22 @@

Query Builder Tutorial

- -

The query builder helps you to make a query in the form of the Corpus Query -Language (CQL) to your text. You can use the CQL to filter out various types of -text parameters, for example, a specific word, a lemma, or you can set part-of-speech +

Overview

+

The query builder can be accessed via "My Corpora" or "Corpus Analysis" in the sidebar options. +Select the desired corpus and click on the "Analyze" and then "Concordance" +buttons to open the query builder.

+

The query builder uses the Corpus Query Language (CQL) to help you make a query for analyzing your texts. +In this way, it is possible to filter out various types of text parameters, for +example, a specific word, a lemma, or you can set part-of-speech tags (pos) that indicate the type of word you are looking for (a noun, an adjective, etc.). In addition, you can also search for structural attributes, or specify your query for a token (word, lemma, pos) via entity typing. And of -course everything can be combined. You can find examples for different queries -under the tab "Examples".

-

+course, the different text parameters can be combined.

+

Tokens and structural attributes can be added by clicking on the "+" button +(the "input marker") in the input field. Elements added are shown as chips. These can +be reorganized using drag and drop. The input marker can also be moved in this way. +Its position shows where new elements will be added.
+A "translation" of your query into Corpus Query Language (CQL) is shown below.

+

Advanced users can make direct use of the Corpus Query Language (CQL) by switching to "expert mode" via the toggle button.

+

The entire input field can be cleared using the red trash icon on the right.


@@ -101,7 +109,9 @@ under the tab "Examples".

this case. For this you can simply string them together:
[word="I"] [word="will" & simple_pos="VERB"] [word="go"].

OR/AND explanation -

+

Tokens that have already been added can also be modified by clicking on the corresponding + pen icon. Click on the "ignore case" box, for example, and the query builder will + not differentiate between upper- and lower- case letters for that respective token.


From f5e98ae6554980e6c5b5fb081b1e51cf4bfffad5 Mon Sep 17 00:00:00 2001 From: Patrick Jentsch Date: Tue, 5 Dec 2023 15:00:21 +0100 Subject: [PATCH 4/4] Add badges to README --- README.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/README.md b/README.md index 30c84ae2..cabdf34b 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,8 @@ # nopaque +![release badge](https://gitlab.ub.uni-bielefeld.de/sfb1288inf/nopaque/-/badges/release.svg) +![pipeline badge](https://gitlab.ub.uni-bielefeld.de/sfb1288inf/nopaque/badges/master/pipeline.svg?ignore_skipped=true) + nopaque bundles various tools and services that provide humanities scholars with DH methods and thus can support their various individual research processes. Using nopaque, researchers can subject digitized sources to Optical Character Recognition (OCR). The resulting text files can then be used as a data basis for Natural Language Processing (NLP). The texts are automatically subjected to various linguistic annotations. The data processed via NLP can then be summarized in the web application as corpora and analyzed by means of an information retrieval system through complex search queries. The range of functions of the web application will be successively extended according to the needs of the researchers. ## Prerequisites and requirements