Triple
T13989384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | School of Medicine & Health Sciences |
E336526
|
entity |
| Predicate | hasDepartment |
P35
|
FINISHED |
| Object |
Department of Medical Laboratory Science
The Department of Medical Laboratory Science is an academic unit that trains students in laboratory-based diagnostic testing, clinical analysis, and research to support medical decision-making and patient care.
|
E1073500
|
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: Department of Medical Laboratory Science | Statement: [School of Medicine & Health Sciences, hasDepartment, Department of Medical Laboratory Science]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Medical Laboratory Science Context triple: [School of Medicine & Health Sciences, hasDepartment, Department of Medical Laboratory Science]
-
A.
School of Medical Laboratory Science
The School of Medical Laboratory Science is an academic unit of Chongqing Medical University specializing in education and research in clinical laboratory and diagnostic sciences.
-
B.
Department of Pathology and Laboratory Medicine
The Department of Pathology and Laboratory Medicine is an academic medical department at the UNC School of Medicine that focuses on diagnosing disease, advancing pathology research, and training future clinicians and scientists.
-
C.
Department of Pathology and Laboratory Medicine
The Department of Pathology and Laboratory Medicine is an academic and clinical department at the University of British Columbia’s Faculty of Medicine that focuses on the study, diagnosis, and research of disease through laboratory-based investigation.
-
D.
Department of Clinical Chemistry
The Department of Clinical Chemistry is a medical laboratory unit at Uppsala University Hospital that specializes in analyzing biological samples to support diagnosis, treatment monitoring, and research.
-
E.
Department of Chemical Pathology
The Department of Chemical Pathology is an academic and clinical department at the Chinese University of Hong Kong’s Faculty of Medicine specializing in the study, diagnosis, and research of diseases through biochemical and molecular analyses of body fluids.
- 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: Department of Medical Laboratory Science Triple: [School of Medicine & Health Sciences, hasDepartment, Department of Medical Laboratory Science]
Generated description
The Department of Medical Laboratory Science is an academic unit that trains students in laboratory-based diagnostic testing, clinical analysis, and research to support medical decision-making and patient care.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Medical Laboratory Science Target entity description: The Department of Medical Laboratory Science is an academic unit that trains students in laboratory-based diagnostic testing, clinical analysis, and research to support medical decision-making and patient care.
-
A.
School of Medical Laboratory Science
The School of Medical Laboratory Science is an academic unit of Chongqing Medical University specializing in education and research in clinical laboratory and diagnostic sciences.
-
B.
Department of Pathology and Laboratory Medicine
The Department of Pathology and Laboratory Medicine is an academic and clinical department at the University of British Columbia’s Faculty of Medicine that focuses on the study, diagnosis, and research of disease through laboratory-based investigation.
-
C.
Department of Pathology and Laboratory Medicine
The Department of Pathology and Laboratory Medicine is an academic medical department at the UNC School of Medicine that focuses on diagnosing disease, advancing pathology research, and training future clinicians and scientists.
-
D.
Department of Clinical Chemistry
The Department of Clinical Chemistry is a medical laboratory unit at Uppsala University Hospital that specializes in analyzing biological samples to support diagnosis, treatment monitoring, and research.
-
E.
Department of Chemical Pathology
The Department of Chemical Pathology is an academic and clinical department at the Chinese University of Hong Kong’s Faculty of Medicine specializing in the study, diagnosis, and research of diseases through biochemical and molecular analyses of body fluids.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb22e388190904fc87765176c91 |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac9604cc819088cde0ad8271ad48 |
completed | May 6, 2026, 9:03 p.m. |
| NEDg | Description generation | batch_69fbad35be6c8190aa329fa947cbdcd9 |
completed | May 6, 2026, 9:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fbae42ef2c8190b653d95de94042bc |
completed | May 6, 2026, 9:10 p.m. |
Created at: April 9, 2026, 10:18 p.m.