When you upload a Word document, you can now convert the existing content controls in XBRL Tagger. XBRL Tagger converts them into editable text ranges, applies prepared XBRL tags and automatically distributes nested ranges to separate layers. You edit the converted text ranges like text ranges you tagged manually, for example by adjusting the start and end of a tag directly in XBRL Tagger.
Converting content controls is particularly useful if you can no longer maintain them in Disclosure Management or MS Word and want to edit the tags in XBRL Tagger only. The conversion is optional and performed once: when you import a new file version, XBRL Tagger carries over the converted text ranges and any other existing tags as usual, but does not import the content controls of the new file as tags again. For details, see Converting Content Controls in XBRL Tagger.
In XBRL Tagger, you can now create up to 100 layers per Word or PDF document instead of 20. This lets you map even extensive reports with many overlapping tags completely. The Layers drop-down list stays within the visible area and can be scrolled. For details, see Working with Layers.
The Find in document function (Ctrl+F) in XBRL Tagger now lets you search Word and PDF documents for words and passages, including text that has not been tagged yet. The search also finds assigned tags by their element label or technical name. XBRL Tagger highlights the matches, and you can move between them. You can narrow the search with the Match case and Match whole word options. Previously, you could only find untagged text by scrolling. In large reports, you can now go directly to the passages you want to tag or review. For details, see Searching for Text in Documents.
The Clipboard in XBRL Tagger now keeps copied mappings when you open another document. XBRL Tagger saves the clipboard content per user, and the content remains available after you reload the browser. Previously, XBRL Tagger cleared the clipboard each time you loaded a document. You can now paste mappings into other documents instead of creating them again. XBRL Tagger marks clipboard entries that cannot be applied in the open document. For details, see Reusing Mappings with the Clipboard.
The Document outline in XBRL Tagger is now also available for PDF documents. Previously, the document outline was only available for Word documents. You can now find tagged items in PDF documents through the outline instead of searching the document for them. For details, see Using the Document Outline.
If you reject the removal of a text tag during the roll-forward review in XBRL Tagger and apply the changes to the document, XBRL Tagger now moves the affected tag to the Clipboard. Previously, the tag was lost in this case, so rejecting had no effect. The mapping is now kept: you can apply the tag manually to a passage in the new document instead of creating it again. For details, see Using the Tag Update Preview.
After an AI tagging run, you can now check the suggested tags in advance in a review window instead of only applying them directly. This keeps you in control of what is actually applied to your document and avoids having to correct faulty tags afterwards. If you trust the suggestions, you can continue to apply them directly without review, as before. For details, see Reviewing AI Tagging Suggestions.
Your decisions in the review window after an AI tagging run are saved automatically as soon as you approve, reject, or set a tag to pending. This is especially useful for a larger number of suggested tags: you can pause the review at any time and continue later without losing decisions you've already made. Tags are only applied to the document once you explicitly confirm this. For details, see Reviewing AI Tagging Suggestions.
In the review window — both after a roll-forward and after an AI tagging run — you can now select multiple tags at once using checkboxes, including a checkbox to mark the entire list, and approve, reject, or reset them to pending together with a single click. This saves you from working through longer lists one entry at a time. The previous Cancel and Save buttons have been combined into a single Close button, since every decision is already saved automatically. For details, see Reviewing AI Tagging Suggestions and Using the Tag Update Preview.
Tagging files that still have an outstanding review after importing a new file version are now immediately recognizable in the dashboard by the addition "(Pending Review)" after the file name. This saves you from opening each file individually to find out why editing or a new import is blocked. The indicator disappears automatically once the review is completed or discarded. For details, see Dashboard.
Certain elements of the KVK taxonomy ("-all" elements) are not intended for tagging. These can no longer be dragged from the taxonomy tree onto the document; a tooltip explains why the element can't be used. This helps you avoid invalid tags that would otherwise only surface later, during validation or generation of the XBRL report, and have to be corrected. For details, see Tagging a Document Manually.
Search in the XBRL Tagger dashboard now also finds tagging files by their taxonomy or reporting requirement, for example by typing "IFRS", "KVK", or "EFRAG" – in addition to the existing search by file and report name. This makes it easier to find reports again when you work with many tagging files across different taxonomies and reporting requirements. For details, see Dashboard.
Opening the report settings now automatically derives the extension prefix and target namespace from the company name on file, even if you don't edit the name field. This means a freshly opened document can be saved right away, without having to retype the company name just to trigger the derivation. Existing values are never overwritten. For details, see Configuring Document Settings.
Automatically entered report settings
This content was generated using AI and reviewed by Lucanet subject matter experts before publication.
