Triple
T14254587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medical Subject Headings |
E353351
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object |
Unified Medical Language System
The Unified Medical Language System is a comprehensive set of files and software from the U.S. National Library of Medicine that integrates and standardizes numerous biomedical vocabularies and coding systems to support interoperability and advanced information retrieval in healthcare and research.
|
E1089726
|
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: Unified Medical Language System | Statement: [Medical Subject Headings, relatedTo, Unified Medical Language System]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unified Medical Language System Context triple: [Medical Subject Headings, relatedTo, Unified Medical Language System]
-
A.
SNOMED International
SNOMED International is a global not-for-profit organization responsible for developing and promoting the SNOMED CT clinical terminology standard used in healthcare systems worldwide.
-
B.
SNOMED CT
SNOMED CT is a comprehensive, multilingual clinical healthcare terminology used worldwide to standardize the recording and sharing of medical information in electronic health records.
-
C.
Medical Subject Headings
Medical Subject Headings (MeSH) is a comprehensive controlled vocabulary thesaurus used for indexing, cataloging, and searching biomedical and health-related information.
-
D.
Regenstrief Medical Record System
The Regenstrief Medical Record System is an early, pioneering electronic medical record platform that helped shape modern health informatics and clinical data management practices.
-
E.
Regenstrief Institute LOINC Committee
The Regenstrief Institute LOINC Committee is the expert governing body responsible for developing, maintaining, and overseeing the Logical Observation Identifiers Names and Codes (LOINC) standard for health data interoperability.
- 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: Unified Medical Language System Triple: [Medical Subject Headings, relatedTo, Unified Medical Language System]
Generated description
The Unified Medical Language System is a comprehensive set of files and software from the U.S. National Library of Medicine that integrates and standardizes numerous biomedical vocabularies and coding systems to support interoperability and advanced information retrieval in healthcare and research.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Unified Medical Language System Target entity description: The Unified Medical Language System is a comprehensive set of files and software from the U.S. National Library of Medicine that integrates and standardizes numerous biomedical vocabularies and coding systems to support interoperability and advanced information retrieval in healthcare and research.
-
A.
SNOMED International
SNOMED International is a global not-for-profit organization responsible for developing and promoting the SNOMED CT clinical terminology standard used in healthcare systems worldwide.
-
B.
SNOMED CT
SNOMED CT is a comprehensive, multilingual clinical healthcare terminology used worldwide to standardize the recording and sharing of medical information in electronic health records.
-
C.
Medical Subject Headings
Medical Subject Headings (MeSH) is a comprehensive controlled vocabulary thesaurus used for indexing, cataloging, and searching biomedical and health-related information.
-
D.
Regenstrief Medical Record System
The Regenstrief Medical Record System is an early, pioneering electronic medical record platform that helped shape modern health informatics and clinical data management practices.
-
E.
Regenstrief Institute LOINC Committee
The Regenstrief Institute LOINC Committee is the expert governing body responsible for developing, maintaining, and overseeing the Logical Observation Identifiers Names and Codes (LOINC) standard for health data interoperability.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6297f38c819090d7c7fd8bfa2e9e |
completed | April 14, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd325c98288190ba035fb5cc5bcf6b |
completed | May 8, 2026, 12:46 a.m. |
| NEDg | Description generation | batch_69fd33cba18481908f2dfe358017f11b |
completed | May 8, 2026, 12:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd346ffb9c81909ec28e514ea5451b |
completed | May 8, 2026, 12:55 a.m. |
Created at: April 10, 2026, 1:09 a.m.