@inproceedings{pannitto-etal-2026-survey,
title = "Survey of Tools for Manual Linguistic Annotation: Supporting Diversity through Interactive Exploration",
author = "Pannitto, Ludovica and
Dobrovoljc Zor, Kaja and
Guillaume, Bruno",
editor = "Piperidis, Stelios and
Bel, N{\'u}ria and
van den Heuvel, Henk and
Ide, Nancy and
Krek, Simon and
Toral, Antonio",
booktitle = "Proceedings of the Fifteenth Language Resources and Evaluation Conference",
month = may,
year = "2026",
address = "Palma de Mallorca, Spain",
publisher = "ELRA Language Resource Association",
url = "https://aclanthology.org/2026.lrec-1.905/",
doi = "10.63317/4u4be6bbtj8e",
pages = "11562--11573",
abstract = "Manual annotation tools are core infrastructure for corpus creation, enabling the development of linguistically informed language resources relevant for both linguistic discovery and computational applications. We present a comprehensive survey of 21 tools supporting morphosyntactic and multi-word expression annotation, systematically documenting more than 50 features relevant for annotation workflows{---}from software architecture and usability to linguistic coverage and annotation scope. The survey results are published as an open dataset and made accessible through an interactive online platform that allows users to filter and compare tools according to their specific needs. Our initial analysis highlights a robust and open ecosystem of annotation tools, but advanced needs for complex and language-independent annotation are inconsistently addressed."
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<abstract>Manual annotation tools are core infrastructure for corpus creation, enabling the development of linguistically informed language resources relevant for both linguistic discovery and computational applications. We present a comprehensive survey of 21 tools supporting morphosyntactic and multi-word expression annotation, systematically documenting more than 50 features relevant for annotation workflows—from software architecture and usability to linguistic coverage and annotation scope. The survey results are published as an open dataset and made accessible through an interactive online platform that allows users to filter and compare tools according to their specific needs. Our initial analysis highlights a robust and open ecosystem of annotation tools, but advanced needs for complex and language-independent annotation are inconsistently addressed.</abstract>
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%0 Conference Proceedings
%T Survey of Tools for Manual Linguistic Annotation: Supporting Diversity through Interactive Exploration
%A Pannitto, Ludovica
%A Dobrovoljc Zor, Kaja
%A Guillaume, Bruno
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F pannitto-etal-2026-survey
%X Manual annotation tools are core infrastructure for corpus creation, enabling the development of linguistically informed language resources relevant for both linguistic discovery and computational applications. We present a comprehensive survey of 21 tools supporting morphosyntactic and multi-word expression annotation, systematically documenting more than 50 features relevant for annotation workflows—from software architecture and usability to linguistic coverage and annotation scope. The survey results are published as an open dataset and made accessible through an interactive online platform that allows users to filter and compare tools according to their specific needs. Our initial analysis highlights a robust and open ecosystem of annotation tools, but advanced needs for complex and language-independent annotation are inconsistently addressed.
%R 10.63317/4u4be6bbtj8e
%U https://aclanthology.org/2026.lrec-1.905/
%U https://doi.org/10.63317/4u4be6bbtj8e
%P 11562-11573
Markdown (Informal)
[Survey of Tools for Manual Linguistic Annotation: Supporting Diversity through Interactive Exploration](https://aclanthology.org/2026.lrec-1.905/) (Pannitto et al., LREC 2026)
ACL