ArticleNucleic acids research2020
TeamTat: a collaborative text annotation tool.
Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Microbial named entity recognition and normalisation for AI-assisted literature review and meta-analysis.Bioinformatics (Oxford, England) · 2026Pooled it
- The DSMZ Digital Diversity Annotation Hub: a pipeline for database expansion via text mining and human curation.Journal of integrative bioinformatics · 2026Article
- Cell phenotypes in the biomedical literature: a systematic analysis and text mining corpus.bioRxiv : the preprint server for biology · 2026Article
- AI in biocuration: challenges, opportunities, and a roadmap for sustainable integration.Bioinformatics advances · 2026Article
- Integrating text mining and knowledge graph to enhance biopharmaceutical process optimization.PloS one · 2026Article
- Enhancing biomedical relation extraction with directionality.Bioinformatics (Oxford, England) · 2025Article
- PDF Entity Annotation Tool (PEAT).Journal of open source software · 2025Article
- Article
- Gut microbiome-mediated epigenetic modifications in gastric cancer: a comprehensive multiomics analysis.Frontiers in cellular and infection microbiology · 2025Article
- Dataset from a human-in-the-loop approach to identify functionally important protein residues from literature.Scientific data · 2024Article
- EnzChemRED, a rich enzyme chemistry relation extraction dataset.Scientific data · 2024Article
- Functional implications of glycans and their curation: insights from the workshop held at the 16th Annual International Biocuration Conference in Padua, Italy.Database : the journal of biological databases and curation · 2024Article
- The biomedical relationship corpus of the BioRED track at the BioCreative VIII challenge and workshop.Database : the journal of biological databases and curation · 2024Article
- Vocabulary Matters: An Annotation Pipeline and Four Deep Learning Algorithms for Enzyme Named Entity Recognition.Journal of proteome research · 2024Article
- Classifying early infant feeding status from clinical notes using natural language processing and machine learning.Scientific reports · 2024Article
- MetaTron: advancing biomedical annotation empowering relation annotation and collaboration.BMC bioinformatics · 2024Article
- Complementary and Integrative Health Information in the literature: its lexicon and named entity recognition.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Clinical entity-aware domain adaptation in low resource setting for inflammatory bowel disease.Frontiers in artificial intelligence · 2024Article
- Automatic classification of experimental models in biomedical literature to support searching for alternative methods to animal experiments.Journal of biomedical semantics · 2023Article
- Extract antibody and antigen names from biomedical literature.BMC bioinformatics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Manually annotated data is key to developing text-mining and information-extraction algorithms. However, human annotation requires considerable time, effort and expertise. Given the rapid growth of biomedical literature, it is paramount to build tools that facilitate speed and maintain expert quality. While existing text annotation tools may provide user-friendly interfaces to domain experts, limited support is available for figure display, project management, and multi-user team annotation. In response, we developed TeamTat (https://www.teamtat.org), a web-based annotation tool (local setup available), equipped to manage team annotation projects engagingly and efficiently. TeamTat is a novel tool for managing multi-user, multi-label document annotation, reflecting the entire production life cycle. Project managers can specify annotation schema for entities and relations and select annotator(s) and distribute documents anonymously to prevent bias. Document input format can be plain text, PDF or BioC (uploaded locally or automatically retrieved from PubMed/PMC), and output format is BioC with inline annotations. TeamTat displays figures from the full text for the annotator's convenience. Multiple users can work on the same document independently in their workspaces, and the team manager can track task completion. TeamTat provides corpus quality assessment via inter-annotator agreement statistics, and a user-friendly interface convenient for annotation review and inter-annotator disagreement resolution to improve corpus quality.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.