Rubrix UIĀ¶
This section contains a quick overview of Rubrix web-appās User Interface (UI).
The web-app has two main pages: the Home page and the Dataset page.
Home pageĀ¶
The Home page is the entry point to Rubrix Datasets. Itās a searchable and sortable list of datasets with the following attributes:
Name
Tags, which displays the
tags
passed to therubrix.log
method. Tags are useful to organize your datasets by project, model, status and any other dataset attribute you can think of.Task, which is defined by the type of
Records
logged into the dataset.Created at, which corresponds to the timestamp of the Dataset creation. Datasets in Rubrix are created by directly using
rb.log
to log a collection of records.Updated at, which corresponds to the timestamp of the last update to this dataset, either by adding/changing/removing some annotations with the UI or via the Python client or the REST API.
Dataset pageĀ¶
The Dataset page is the workspace for exploring and annotating records in a Rubrix Dataset. Every task has its own specialized components, while keeping a similar layout and structure.
Here we describe the search components and the two modes of operation (Explore and Annotation).
The Rubrix Dataset page is driven by search features. The search bar gives users quick filters for easily exploring and selecting data subsets. The main sections of the search bar are following:
Search inputĀ¶
This component enables:
Full-text queries over all record inputs
.
Queries using Elasticsearchās query DSL with the query string syntax, which enables powerful queries for advanced users, using the Rubrix data model. Some examples are:
inputs.text:(women AND feminists)
: records containing the words āwomenā AND āfeministā in the inputs.text field.
inputs.text:(NOT women)
: records NOT containing women in the inputs.text field.
inputs.hypothesis:(not OR don't)
: records containing the word ānotā or the phrase ādonātā in the inputs.hypothesis field.
metadata.format:pdf AND metadata.page_number>1
: records with metadata.format equals pdf and with metadata.page_number greater than 1.
NOT(_exists_:metadata.format)
: records that donāt have a value for metadata.format.
predicted_as:(NOT Sports)
: records which are not predicted with the label Sports
, this is useful when you have many target labels and want to exclude only some of them.
Predictions filtersĀ¶
This component allows filtering by aspects related to predictions, such as:
predicted as, for filtering records by predicted labels,
predicted by, for filtering by prediction_agent (e.g., different versions of a model)
predicted ok or ko, for filtering records whose predictions are (or not) correct with respect to the annotations.
Annotations filtersĀ¶
This component allows filtering by aspects related to annotations, such as:
annotated as, for filtering records by annotated labels,
annotated by, for filtering by annotation_agent (e.g., different human users or dataset versions)
Status filterĀ¶
This component allows filtering by record status:
Default: records without any annotation or edition.
Validated: records with validated annotations.
Edited: records with annotations but not yet validated.
Metadata filtersĀ¶
This component allows filtering by metadata fields. The list of filters is dynamic and itās created with the aggregations of metadata fields included in any of the logged records.
Active query parametersĀ¶
This component show the current active search params, it allows removing each individual param as well as all params at once.
Explore modeĀ¶
This mode enables users to explore a records in a dataset. Different tasks provide different visualizations tailored for the task.
Annotation modeĀ¶
This mode enables users to add and modify annotations, while following the same interaction patterns as in the explore mode (e.g., using filters and advanced search), as well as novel features such as bulk annotation for a given set of search params.