The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
Corpus annotation for mining biomedical events from literature
Open accessAbstract
BACKGROUND: Advanced Text Mining (TM) such as semantic enrichment of papers, event or relation extraction, and intelligent Question Answering have increasingly attracted attention in the bio-medical domain. For such attempts to succeed, text annotation from the biological point of view is indispensable. However, due to the complexity of the task, semantic annotation has never been tried on a large scale, apart from relatively simple term annotation. RESULTS: We have completed a new type of semantic annotation, event annotation, which is an addition to the existing annotations in the GENIA corpus. The corpus has already been annotated with POS (Parts of Speech), syntactic trees, terms, etc. The new annotation was made on half of the GENIA corpus, consisting of 1,000 Medline abstracts. It contains 9,372 sentences in which 36,114 events are identified. The major challenges during event annotation were (1) to design a scheme of annotation which meets specific requirements of text annotation, (2) to achieve biology-oriented annotation which reflect biologists' interpretation of text, and (3) to ensure the homogeneity of annotation quality across annotators. To meet these challenges, we introduced new concepts such as Single-facet Annotation and Semantic Typing, which have collectively contributed to successful completion of a large scale annotation. CONCLUSION: The resulting event-annotated corpus is the largest and one of the best in quality among similar annotation efforts. We expect it to become a valuable resource for NLP (Natural Language Processing)-based TM in the bio-medical domain.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
Building a Large Annotated Corpus of English: The Penn Treebank
Marcus, M. (1993) · doi:10.21236/ada273556 · Cited by 7,405
A Extensible Markup Language XML
(2009) · Foundations of Semantic Web Technologies · doi:10.1201/9781420090512-18 · Cited by 4,824
The unified medical language system (UMLS): integrating biomedical terminology
Bodenreider, O. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh061 · Cited by 4,356
Pustejovsky, J. (2004) · Semantics · doi:10.1093/oso/9780195136975.003.0018 · Cited by 3,963
Baker, C. F., Fillmore, C. J., & Lowe, J. B. (1998) · Proceedings of the 36th annual meeting on Association for Computational Linguistics - · doi:10.3115/980845.980860 · Cited by 2,518
GENIA corpus—a semantically annotated corpus for bio-textmining
Kim, J.-D., Ohta, T., Tateisi, Y., & Tsujii, J. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg1023 · Cited by 1,232
Self-citationConceptual Information Processing
(1975) · Elsevier eBooks · doi:10.1016/c2013-0-12220-9 · Cited by 1,225
Relations in biomedical ontologies
Smith, B., Ceusters, W., Klagges, B., Köhler, J., Kumar, A., Lomax, J., Mungall, C., Neuhaus, F., Rector, A. L., & Rosse, C. (2005) · Genome Biology · doi:10.1186/gb-2005-6-5-r46 · Cited by 1,018
Fish Oil, Raynaud's Syndrome, and Undiscovered Public Knowledge
Swanson, D. R. (1986) · Perspectives in Biology and Medicine · doi:10.1353/pbm.1986.0087 · Cited by 866
Cited by
HH-suite3 for fast remote homology detection and deep protein annotation
Steinegger, M., Meier, M., Mirdita, M., Vöhringer, H., Haunsberger, S. J., & Söding, J. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-3019-7 · Cited by 1,145
The BioScope corpus: biomedical texts annotated for uncertainty, negation and their scopes
Vincze, V., Szarvas, G., Farkas, R., Móra, G., & Csirik, J. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-s11-s9 · Cited by 421
Concept annotation in the CRAFT corpus
Bada, M., Eckert, M., Evans, D., Garcia, K., Shipley, K., Sitnikov, D., Baumgartner, W. A., Cohen, K. B., Verspoor, K., Blake, J. A., et al. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-161 · Cited by 272
A neural network multi-task learning approach to biomedical named entity recognition
Crichton, G., Pyysalo, S., Chiu, B., & Korhonen, A. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1776-8 · Cited by 229
Campillos-Llanos, L., Valverde-Mateos, A., Capllonch-Carrión, A., & Moreno-Sandoval, A. (2021) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-021-01395-z · Cited by 65
Metadata
- Authors
- Kim, J.-D., Ohta, T., & Tsujii, J.
- Venue
- BMC Bioinformatics
- Published
- 2008-01-08
- Volume
- 9
- Issue
- 1
- Pages
- 10-10
- ISSN
- 1471-2105 (ISSN-L)
- OpenAlex
- W2149803936
- Cited by
- 395
- References
- 59
- FWCI
- 18.12
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Corpus annotation for mining biomedical events from literature. https://app.cochat.ai/papers/10.1186/1471-2105-9-10
- The paper
- Kim, J.-D., Ohta, T., & Tsujii, J. (2008). Corpus annotation for mining biomedical events from literature. BMC Bioinformatics. https://doi.org/10.1186/1471-2105-9-10
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
