Triple

T861496
Position Surface form Disambiguated ID Type / Status
Subject Federal Ministry of Health (Germany) E18606 entity
Predicate oversees P46 FINISHED
Object German Institute for Medical Documentation and Information
The German Institute for Medical Documentation and Information is a federal agency responsible for managing health data, medical information systems, and standards to support healthcare and health policy in Germany.
E102200 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: German Institute for Medical Documentation and Information | Statement: [Federal Ministry of Health (Germany), oversees, German Institute for Medical Documentation and Information]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: German Institute for Medical Documentation and Information
Context triple: [Federal Ministry of Health (Germany), oversees, German Institute for Medical Documentation and Information]
  • A. Robert Koch Institute
    The Robert Koch Institute is Germany’s national public health institute, renowned for its research in infectious diseases, epidemiology, and disease prevention.
  • B. University Medical Center Göttingen
    University Medical Center Göttingen is a major academic teaching hospital and research institution in Göttingen, Germany, providing specialized medical care while supporting clinical education and biomedical research.
  • C. Charité – Universitätsmedizin Berlin
    Charité – Universitätsmedizin Berlin is one of Europe’s largest and most renowned university hospitals, combining cutting-edge medical research, teaching, and patient care in partnership with Berlin’s major universities.
  • D. German Council of Science and Humanities
    The German Council of Science and Humanities is a key advisory body in Germany that provides expert recommendations on the development of science, research, and higher education policy to the federal and state governments.
  • E. Helmholtz Association
    The Helmholtz Association is Germany’s largest scientific research organization, operating a network of national research centers that conduct long-term, large-scale research in areas such as energy, health, environment, and technology.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: German Institute for Medical Documentation and Information
Triple: [Federal Ministry of Health (Germany), oversees, German Institute for Medical Documentation and Information]
Generated description
The German Institute for Medical Documentation and Information is a federal agency responsible for managing health data, medical information systems, and standards to support healthcare and health policy in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: German Institute for Medical Documentation and Information
Target entity description: The German Institute for Medical Documentation and Information is a federal agency responsible for managing health data, medical information systems, and standards to support healthcare and health policy in Germany.
  • A. Robert Koch Institute
    The Robert Koch Institute is Germany’s national public health institute, renowned for its research in infectious diseases, epidemiology, and disease prevention.
  • B. University Medical Center Göttingen
    University Medical Center Göttingen is a major academic teaching hospital and research institution in Göttingen, Germany, providing specialized medical care while supporting clinical education and biomedical research.
  • C. Charité – Universitätsmedizin Berlin
    Charité – Universitätsmedizin Berlin is one of Europe’s largest and most renowned university hospitals, combining cutting-edge medical research, teaching, and patient care in partnership with Berlin’s major universities.
  • D. German Council of Science and Humanities
    The German Council of Science and Humanities is a key advisory body in Germany that provides expert recommendations on the development of science, research, and higher education policy to the federal and state governments.
  • E. Helmholtz Association
    The Helmholtz Association is Germany’s largest scientific research organization, operating a network of national research centers that conduct long-term, large-scale research in areas such as energy, health, environment, and technology.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a4938ce8688190a24bdfef82ba7d21 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac6631408190a19b83126fa86100 completed March 1, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3c3d2fc8190b9f76d31528feeb6 completed March 4, 2026, 3:15 a.m.
NEDg Description generation batch_69a7a558c1308190810a139ad24dfc9d completed March 4, 2026, 3:22 a.m.
NED2 Entity disambiguation (via description) batch_69a7a5e744188190ae30544753fb9399 completed March 4, 2026, 3:24 a.m.
Created at: March 1, 2026, 7:39 p.m.