@inproceedings{bittner-etal-2026-developing,
title = "Developing Literature Annotation Guidelines for Representing Normal Physiology in Biolink-Compatible Knowledge Graphs",
author = "Bittner, Madeline and
Rogers, Willie and
Demner-Fushman, Dina and
Scheuermann, Richard and
Diller, Matthew",
editor = "Demner-Fushman, Dina and
Ananiadou, Sophia and
Roberts, Kirk and
Tsujii, Junichi",
booktitle = "{B}io{NLP} 2026",
month = jul,
year = "2026",
address = "San Diego, California",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.bionlp-1.59/",
pages = "718--728",
ISBN = "979-8-89176-434-7",
abstract = "Much of our knowledge about anatomy and physiology is found in text format in research papers and medical textbooks. For an information system to have access to this knowledge, extracting and translating it into a computable format that can be stored in an ontology or knowledge graph is advantageous. Unfortunately, existing text mining corpora, which are needed to train and evaluate data mining models, are old and consist almost entirely of research papers, which rarely contain complete information needed to capture complex normal physiological processes and, subsequently, understand the pathophysiology of a disease. As a first step to filling in this gap, we have developed a guide for annotating medical textbooks for physiological events and entities involved in these events. In addition to providing our guidelines and describing the guideline development process, we analyze the coverage of normal physiology in existing ontologies."
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<abstract>Much of our knowledge about anatomy and physiology is found in text format in research papers and medical textbooks. For an information system to have access to this knowledge, extracting and translating it into a computable format that can be stored in an ontology or knowledge graph is advantageous. Unfortunately, existing text mining corpora, which are needed to train and evaluate data mining models, are old and consist almost entirely of research papers, which rarely contain complete information needed to capture complex normal physiological processes and, subsequently, understand the pathophysiology of a disease. As a first step to filling in this gap, we have developed a guide for annotating medical textbooks for physiological events and entities involved in these events. In addition to providing our guidelines and describing the guideline development process, we analyze the coverage of normal physiology in existing ontologies.</abstract>
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%0 Conference Proceedings
%T Developing Literature Annotation Guidelines for Representing Normal Physiology in Biolink-Compatible Knowledge Graphs
%A Bittner, Madeline
%A Rogers, Willie
%A Demner-Fushman, Dina
%A Scheuermann, Richard
%A Diller, Matthew
%Y Demner-Fushman, Dina
%Y Ananiadou, Sophia
%Y Roberts, Kirk
%Y Tsujii, Junichi
%S BioNLP 2026
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California
%@ 979-8-89176-434-7
%F bittner-etal-2026-developing
%X Much of our knowledge about anatomy and physiology is found in text format in research papers and medical textbooks. For an information system to have access to this knowledge, extracting and translating it into a computable format that can be stored in an ontology or knowledge graph is advantageous. Unfortunately, existing text mining corpora, which are needed to train and evaluate data mining models, are old and consist almost entirely of research papers, which rarely contain complete information needed to capture complex normal physiological processes and, subsequently, understand the pathophysiology of a disease. As a first step to filling in this gap, we have developed a guide for annotating medical textbooks for physiological events and entities involved in these events. In addition to providing our guidelines and describing the guideline development process, we analyze the coverage of normal physiology in existing ontologies.
%U https://aclanthology.org/2026.bionlp-1.59/
%P 718-728
Markdown (Informal)
[Developing Literature Annotation Guidelines for Representing Normal Physiology in Biolink-Compatible Knowledge Graphs](https://aclanthology.org/2026.bionlp-1.59/) (Bittner et al., BioNLP 2026)
ACL