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193 lines
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193 lines
12 KiB
Markdown
# neat: named entity annotation tool
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#### version 0.1
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---
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---
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### Table of contents
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[1. Introduction](https://github.com/qurator-spk/neat/blob/master/README.md#1-introduction)
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[2. User Guide](https://github.com/qurator-spk/neat/blob/master/README.md#2-user-guide)
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[2.1 Technical requirements](https://github.com/qurator-spk/neat/blob/master/README.md#21-technical-requirements)
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[2.2 Installation](https://github.com/qurator-spk/neat/blob/master/README.md#22-installation)
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[2.3 Data format](https://github.com/qurator-spk/neat/blob/master/README.md#23-data-format)
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[2.4 Data preparation](https://github.com/qurator-spk/neat/blob/master/README.md#24-data-preparation)
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[2.5 Provenance](https://github.com/qurator-spk/neat/blob/master/README.md#25-provenance)
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[2.6 Keyboard navigation](https://github.com/qurator-spk/neat/blob/master/README.md#26-keyboard-navigation)
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[2.7 Mouse navigation](https://github.com/qurator-spk/neat/blob/master/README.md#27-mouse-navigation)
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[2.8 Image support](https://github.com/qurator-spk/neat/blob/master/README.md#28-image-support)
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[2.9 Saving progress](https://github.com/qurator-spk/neat/blob/master/README.md#29-saving-progress)
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[3. Annotation Guidelines](https://github.com/qurator-spk/neat/blob/master/README.md#3-annotation-guidelines)
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### 1. Introduction
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[neat](https://github.com/qurator-spk/neat) is a simple, browser-based tool for editing and annotating text with named entities to produce a corpus for training/testing/evaluation. It can be used to add or correct named entity BIO-tags in a TSV file and to correct the token text or tokenization (e.g. due to OCR/segmentation errors).
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[neat](https://github.com/qurator-spk/neat) is developed at the [Berlin State Library](https://staatsbibliothek-berlin.de/) for data annotation in the context of the [SoNAR-IDH](https://sonar.fh-potsdam.de/) project and the [QURATOR](https://qurator.ai/) project.
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### 2. User Guide
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#### 2.1 Technical Requirements
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[neat](https://github.com/qurator-spk/neat) runs locally as a pure HTML+JavaScript webpage in your web browser. No software needs to be installed, but JavaScript has to be enabled in the browser.
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#### 2.2. Installation
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Simply clone the repo using ``git clone https://github.com/qurator-spk/neat.git`` or download the [ZIP](https://github.com/qurator-spk/neat/archive/master.zip). Make sure you have at minimum ``neat.html`` and ``neat.js`` residing in a local directory, then it is sufficient to just open ``neat.html`` in a browser. Any fairly recent browser should work, but only Chrome and Firefox are tested.
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#### 2.3 Data format
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The data format is based on the format used in the [GermEval2014 Named Entity Recognition Shared Task](https://sites.google.com/site/germeval2014ner/data). Text is encoded as one token per line, with name spans encoded in the BIO-scheme, provided as tab-separated values:
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* the first column contains either a `#`, which signals the source the sentence is cited from, or
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* the token position within the sentence ``>=1``
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* sentence boundaries are indicated by ``0``
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* the second column contains the token ``text``
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* outer entity spans are encoded in the third column ``NE-TAG``
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* embedded entity spans are encoded in the fourth column ``NE-EMB``
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Example (simple):
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```tsv
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No. TOKEN NE-TAG NE-EMB
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# https://example.url
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1 Donnerstag O O
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2 , O O
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3 1 O O
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4 . O O
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5 Januar O O
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6 . O O
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0 O O
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1 Berliner B-ORG B-LOC
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2 Tageblatt I-ORG O
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3 . O O
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0 O O
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1 Nr O O
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2 . O O
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3 1 O O
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4 . O O
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0 O O
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1 Seite O O
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2 3 O O
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```
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For our purposes we extend this format by adding
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* a fifth column for an ``ID`` for the outer ``NE-TAG`` from an authority file (in this case, the [GND](https://www.dnb.de/EN/Professionell/Standardisierung/GND/gnd_node.html) is used)
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* column six for use as a variable ``url_id`` (see [Image Support](https://github.com/qurator-spk/neat/blob/master/README.md#28-image-support) for further details)
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* finally, columns 7+ are used for storing ``left,right,top,bottom`` pixel coordinates for facsimile snippets
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Example (full):
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```tsv
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No. TOKEN NE-TAG NE-EMB GND-ID url_id left,right,top,bottom
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# https://example.url/iiif/left,right,top,bottom/full/0/default.jpg
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1 Donnerstag O O - 0 174,352,358,390
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2 , O O - 0 174,352,358,390
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3 1 O O - 0 367,392,361,381
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4 . O O - 0 370,397,352,379
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5 Januar O O - 0 406,518,358,386
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6 . O O - 0 406,518,358,386
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0
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1 Berliner B-ORG B-LOC 1086206452 0 816,984,358,388
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2 Tageblatt I-ORG O 1086206452 0 1005,1208,360,387
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3 . O O - 0 1005,1208,360,387
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0
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1 Nr O O - 0 1237,1288,360,382
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2 . O O - 0 1237,1288,360,382
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3 1 O O - 0 1304,1326,361,381
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4 . O O - 0 1304,1326,361,381
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0
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1 Seite O O - 0 1837,1926,361,392
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2 3 O O - 0 1939,1967,364,385
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```
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#### 2.4 Data preparation
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The source data that is used for annotation are OCR results in [PAGE-XML](https://github.com/PRImA-Research-Lab/PAGE-XML) format. We provide a [Python tool](https://github.com/qurator-spk/page2tsv) that supports the transformation of [PAGE-XML](https://github.com/PRImA-Research-Lab/PAGE-XML) OCR files into the [TSV format](https://github.com/qurator-spk/neat/blob/master/README.md#23-data-format) required for use with [neat](https://github.com/qurator-spk/neat).
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#### 2.5 Provenance
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The processing pipeline applied at the Berlin State Library comprises the follows steps:
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1. Layout Analysis & Textline Extraction
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Layout Analysis & Textline Extraction @[sbb_textline_detector](https://github.com/qurator-spk/sbb_textline_detector)
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2. OCR & Word Segmentation
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OCR is based on [OCR-D](https://github.com/OCR-D)'s [ocrd_tesserocr](https://github.com/OCR-D/ocrd_tesserocr) which requires [Tesseract](https://github.com/tesseract-ocr/tesseract) **>= 4.1.0**. The [GT4HistOCR_2000000](https://ub-backup.bib.uni-mannheim.de/~stweil/ocrd-train/data/GT4HistOCR_2000000.traineddata) model, which is [trained](https://github.com/tesseract-ocr/tesstrain/wiki/GT4HistOCR) on the [GT4HistOCR](https://zenodo.org/record/1344132) corpus, is used. Further details are available in the [paper](https://arxiv.org/abs/1809.05501).
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3. TSV Transformation
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A simple [Python tool](https://github.com/qurator-spk/page2tsv) is used for the transformation of the OCR results in [PAGE-XML](https://github.com/PRImA-Research-Lab/PAGE-XML) to [TSV](https://github.com/qurator-spk/neat/blob/master/docs/README.md#23-data-format).
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4. Tokenization
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For tokenization, [SoMaJo](https://github.com/tsproisl/SoMaJo) is used.
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5. Named Entity Recognition
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For Named Entity Recognition, a [BERT-Base](https://github.com/google-research/bert) model was trained for noisy OCR texts with historical spelling variation. [sbb_ner](https://github.com/qurator-spk/sbb_ner) is using a combination of unsupervised training on a large (~2.3m pages) [corpus of German OCR](https://zenodo.org/record/3257041) in combination with supervised training on a small (47k tokens) [annotated corpus](https://github.com/EuropeanaNewspapers/ner-corpora/tree/master/enp_DE.sbb.bio). Further details are available in the [paper](https://corpora.linguistik.uni-erlangen.de/data/konvens/proceedings/papers/KONVENS2019_paper_4.pdf).
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#### 2.6 Keyboard-Navigation
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| Key Combination| Action |
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|:---------|:-------------------------------------------|
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| Left | Move one cell left |
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| Right | Move one cell right |
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| Up | Move one row up |
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| Down | Move one row down |
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| PageDown | Move page down |
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| PageUp | Move page up |
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| Crtl+Up | Move entire table one row up |
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| Crtl+Down| Move entire table one row down |
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|----------|--------------------------------------------|
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| s t | Start new sentence in current row |
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| m e | Merge current row with row above |
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| s p | Create copy of current row |
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| d l | Delete current row |
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|----------|--------------------------------------------|
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| backspace| Set NE-TAG / NE-EMB to "O" |
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| b p | Set NE-TAG / NE-EMB to "B-PER" |
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| b l | Set NE-TAG / NE-EMB to "B-LOC" |
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| b o | Set NE-TAG / NE-EMB to "B-ORG" |
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| b w | Set NE-TAG / NE-EMB to "B-WORK" |
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| b c | Set NE-TAG / NE-EMB to "B-CONF" |
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| b e | Set NE-TAG / NE-EMB to "B-EVT" |
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| b t | Set NE-TAG / NE-EMB to "B-TODO" |
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| i p | Set NE-TAG / NE-EMB to "I-PER" |
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| i l | Set NE-TAG / NE-EMB to "I-LOC" |
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| i o | Set NE-TAG / NE-EMB to "I-ORG" |
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| i w | Set NE-TAG / NE-EMB to "I-WORK" |
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| i c | Set NE-TAG / NE-EMB to "I-CONF" |
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| i e | Set NE-TAG / NE-EMB to "I-EVT" |
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| i t | Set NE-TAG / NE-EMB to "I-TODO" |
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|----------|--------------------------------------------|
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| enter | Edit TOKEN or GND-ID |
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| esc | Close TOKEN or GND-ID edit field without |
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| | application of changes. |
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|----------|--------------------------------------------|
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| l a | add one display row |
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| l r | remove on display row (minimum is 5) |
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|----------|--------------------------------------------|
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#### 2.7 Mouse-Navigation
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* use mouse wheel to scroll up and down
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* left-click `<<` and `>>` to move 15 rows up or down
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* left-click `O` in the `NE-TAG` or `NE-EMB` columns to open the drop-down menu and select any of the supported NE-Tags to tag a token or change an existing tag to another one
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* left-click a tag in the `NE-TAG` or `NE-EMB` columns and subsequently select `O` to remove a wrong tag
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* left-click a token in the `TOKEN` column to edit/correct the text content
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* left-click the `POSITION` of a row and select `split` from the drop-down menu to create a copy of the current row
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* left-click the `POSITION` of a row and select `merge` from the drop-down menu to merge the current row with the row above
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* left-click the `POSITION` of a row and select `start-sentence` from the drop-down menu to start a new sentence
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#### 2.8 Image Support
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Provided facsimile images are available online via the [iiif.io](https://iiif.io/) Image API, [neat](https://github.com/qurator-spk/neat) supports the embedding of facsimile snippets into its interface to help with data annotation and correction.
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This further requires that OCR with word segmentation is applied to the image to determine bounding boxes for tokens.
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The iiif-image-url contained in the source ``#`` can then be used as a replacement for ``url_id`` in combination with the token bounding boxes as ``left,right,top,bottom`` to obtain the facsimile snippet url and display the image in the leftmost column. Clicking on the facsimile snippet opens up a new tab with a larger context.
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#### 2.9 Saving progress
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[neat](https://github.com/qurator-spk/neat) runs fully locally in the browser. Therefore it can not automatically save any changes you made to disk. You have to use the `Save Changes` button in order to so manually from time to time. If your browser automatically saves all downloads to your `Downloads` folder, you might want to configure it so that it instead prompts you where to save.
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### 3. Annotation Guidelines
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The most recent version of the [Annotation Guidelines](https://github.com/qurator-spk/neat/blob/master/Annotation_Guidelines.pdf) is included in this repository.
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