| Challenge: | Recent advances in natural language processing (NLP) are fuelled by high quality annotated datasets. |
| Approach: | They introduce Redcoat, a web-based annotation tool that supports collaborative hierarchical entity typing. |
| Outcome: | The proposed annotation tool reduces the time it takes for project creators to set up and distribute projects to annotators and scales the workload depending on the number of active annotator. |
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A Web-based Collaborative Annotation and Consolidation Tool (2020.lrec-1)
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| Challenge: | Annotation tools have a rigid structure, closed back-end and front-end, and are built in a non-user-friendly way rendering them unusable for a large cohort. |
| Approach: | They propose a web-based collaborative annotation and consolidation tool (AWOCATo) that supports varied textual formats and allows users to easily adapt to the annotation task. |
| Outcome: | AWOCATo supports a range of tasks and domains, filling the gap left by the lack of tools that can be used by people with and without programming knowledge. |
KCAT: A Knowledge-Constraint Typing Annotation Tool (P19-3)
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Sheng Lin, Luye Zheng, Bo Chen, Siliang Tang, Zhigang Chen, Guoping Hu, Yueting Zhuang, Fei Wu, Xiang Ren
| Challenge: | Recent years Natural Language Processing community has seen a surge of interest in fine-grained entity typing (FET) given an entity mention (i.e. a sequence of token spans representing an entity), FET aims at uncovering its contextdependent type. |
| Approach: | They propose an efficient Knowledge Constraint Fine-grained Entity Typing Annotation Tool which further improves the entity typing process through entity linking together with some practical functions. |
| Outcome: | The proposed tool improves the entity typing process by linking the candidate types with some practical functions. |
TreeAnnotator: Versatile Visual Annotation of Hierarchical Text Relations (L18-1)
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| Challenge: | TREEANNOTATOR is a browser-based tool for annotating tree-like structures . it provides a wider range of formats and provides graphical annotations . |
| Approach: | They evaluate TREEANNOTATOR, a browser-based tool for annotating tree-like structures, in particular structures that jointly map dependency relations and inclusion hierarchies, as used by Rhetorical Structure Theory. |
| Outcome: | The GUI interface is user-friendly and provides two visualization modes. |
CHAMP: Efficient Annotation and Consolidation of Cluster Hierarchies (2023.emnlp-demo)
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| Challenge: | Various annotation tasks require a complex hierarchical structure over nodes, where each node is a cluster of items. |
| Approach: | They propose an open source tool that incrementally constructs clusters and hierarchy simultaneously over any type of text. |
| Outcome: | The proposed approach significantly reduces annotation time and guarantees transitivity at the cluster and hierarchy levels. |
Enhanced Entity Annotations for Multilingual Corpora (2022.lrec-1)
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| Challenge: | Named Entity Recognition (NER) is a new language for natural language processing. |
| Approach: | They propose to improve the annotation quality of the English Wikipedia tool WEXEA . they propose to use a proven NER system to annotate entities in Wikipedia . |
| Outcome: | The proposed tool can be used to exhaustively annotate entities in Wikipedia articles. |
SLATE: A Super-Lightweight Annotation Tool for Experts (P19-3)
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| Challenge: | a new annotation tool is designed to fill the niche of a lightweight interface for terminal users . current tools are built with direct manipulation via a Graphical User Interface (GUI) this approach is time-consuming and difficult to modify . |
| Approach: | They propose a terminal-based annotation tool that supports multiple annotations . they use a text-based interface that uses almost the entire screen to display documents . |
| Outcome: | The proposed tool is designed to fill the niche of a lightweight interface for users with a terminal-based workflow. |
Hierarchical Entity Typing via Multi-level Learning to Rank (2020.acl-main)
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| Challenge: | Named entity recognition (NER) is a canonical information extraction task that assigns spans to one of a handful of types. |
| Approach: | They propose a hierarchical entity classification method that embraces ontological structure at training and during prediction. |
| Outcome: | The proposed method outperforms previous work on strict accuracy and significantly outperformed previous work. |
HUMAN: Hierarchical Universal Modular ANnotator (2020.emnlp-demos)
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| Challenge: | HUMAN is a web-based annotation tool that covers a variety of annotation tasks on textual and image data. |
| Approach: | They propose a web-based annotation tool that covers a variety of annotation tasks on textual and image data. |
| Outcome: | HUMAN covers a variety of annotation tasks on textual and image data and uses an internal deterministic state machine to chain different tasks in an interdependent manner. |
Paladin: an annotation tool based on active and proactive learning (2021.eacl-demos)
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| Challenge: | Existing tools for active learning focus on the active learning algorithms and provide no user interface thus making it difficult to use for the end-users. |
| Approach: | They present an open-source web-based annotation tool for creating high-quality multi-label document-level datasets that integrates active learning and proactive learning. |
| Outcome: | The proposed tool is designed for multi-label annotation, but it can be adapted to other tasks in single-l Label settings. |
TS-ANNO: An Annotation Tool to Build, Annotate and Evaluate Text Simplification Corpora (2022.acl-demo)
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| Challenge: | Currently, high-quality corpora of this type are rare and often of comparably small size. |
| Approach: | They propose an open-source web application for automatic text simplification. |
| Outcome: | TS-ANNO can be used for i) sentence–wise alignment, ii) rating alignment pairs, w.r.t. simplification transformations, and iv) manual simplification of complex documents. |