Triple

T97370
Position Surface form Disambiguated ID Type / Status
Subject School of Clinical Medicine, University of Cambridge E1961 entity
Predicate hasDepartment P35 FINISHED
Object Department of Obstetrics and Gynaecology, University of Cambridge
The Department of Obstetrics and Gynaecology at the University of Cambridge is an academic and clinical centre focused on research, education, and specialist care in pregnancy, childbirth, and women's reproductive health.
E14770 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 Obstetrics and Gynaecology, University of Cambridge | Statement: [School of Clinical Medicine, University of Cambridge, hasDepartment, Department of Obstetrics and Gynaecology, University of Cambridge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Department of Obstetrics and Gynaecology, University of Cambridge
Context triple: [School of Clinical Medicine, University of Cambridge, hasDepartment, Department of Obstetrics and Gynaecology, University of Cambridge]
  • A. School of Clinical Medicine, University of Cambridge
    The School of Clinical Medicine at the University of Cambridge is the institution’s primary center for medical education, clinical training, and biomedical research.
  • B. Department of Medicine, University of Cambridge
    The Department of Medicine at the University of Cambridge is a major academic and clinical research department focused on advancing medical science and training healthcare professionals within the university’s School of Clinical Medicine.
  • C. Department of Surgery, University of Cambridge
    The Department of Surgery at the University of Cambridge is an academic and clinical department specializing in surgical research, education, and training within the university’s School of Clinical Medicine.
  • D. Department of Public Health and Primary Care, University of Cambridge
    The Department of Public Health and Primary Care at the University of Cambridge is a leading academic center focused on research and teaching in population health, epidemiology, and primary care practice.
  • E. Department of Obstetrics and Gynecology, Duke University
    The Department of Obstetrics and Gynecology at Duke University is a clinical and academic unit specializing in women's reproductive health, pregnancy care, and related research and education within the university's medical center.
  • 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 Obstetrics and Gynaecology, University of Cambridge
Triple: [School of Clinical Medicine, University of Cambridge, hasDepartment, Department of Obstetrics and Gynaecology, University of Cambridge]
Generated description
The Department of Obstetrics and Gynaecology at the University of Cambridge is an academic and clinical centre focused on research, education, and specialist care in pregnancy, childbirth, and women's reproductive health.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Department of Obstetrics and Gynaecology, University of Cambridge
Target entity description: The Department of Obstetrics and Gynaecology at the University of Cambridge is an academic and clinical centre focused on research, education, and specialist care in pregnancy, childbirth, and women's reproductive health.
  • A. School of Clinical Medicine, University of Cambridge
    The School of Clinical Medicine at the University of Cambridge is the institution’s primary center for medical education, clinical training, and biomedical research.
  • B. Department of Medicine, University of Cambridge
    The Department of Medicine at the University of Cambridge is a major academic and clinical research department focused on advancing medical science and training healthcare professionals within the university’s School of Clinical Medicine.
  • C. Department of Surgery, University of Cambridge
    The Department of Surgery at the University of Cambridge is an academic and clinical department specializing in surgical research, education, and training within the university’s School of Clinical Medicine.
  • D. Department of Public Health and Primary Care, University of Cambridge
    The Department of Public Health and Primary Care at the University of Cambridge is a leading academic center focused on research and teaching in population health, epidemiology, and primary care practice.
  • E. Department of Obstetrics and Gynecology, Duke University
    The Department of Obstetrics and Gynecology at Duke University is a clinical and academic unit specializing in women's reproductive health, pregnancy care, and related research and education within the university's medical center.
  • 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_69a24d4862f881908cc8b89d3a78031d completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a24feef1b08190bb9525f71cce053e completed Feb. 28, 2026, 2:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2a3d29e348190820f8a1ed207be2e completed Feb. 28, 2026, 8:14 a.m.
NEDg Description generation batch_69a2a456dc6881909f55e96a91d6d7eb completed Feb. 28, 2026, 8:16 a.m.
NED2 Entity disambiguation (via description) batch_69a2a5b6aca481909c920d2b2f708c56 completed Feb. 28, 2026, 8:22 a.m.
Created at: Feb. 28, 2026, 2:09 a.m.