Triple

T13540246
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Medicine, University of Ruhuna E323363 entity
Predicate hasDepartment P35 FINISHED
Object Department of Obstetrics and Gynaecology
The Department of Obstetrics and Gynaecology is an academic and clinical unit specializing in women’s reproductive health, pregnancy, and childbirth within the medical faculty.
E947545 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 | Statement: [Faculty of Medicine, University of Ruhuna, hasDepartment, Department of Obstetrics and Gynaecology]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Department of Obstetrics and Gynaecology
Context triple: [Faculty of Medicine, University of Ruhuna, hasDepartment, Department of Obstetrics and Gynaecology]
  • A. Department of Obstetrics and Gynaecology
    The Department of Obstetrics and Gynaecology is a clinical academic unit specializing in women’s reproductive health, pregnancy, and childbirth within the Chinese University of Hong Kong’s medical faculty.
  • B. Department of Obstetrics and Gynecology
    The Department of Obstetrics and Gynecology is a medical academic and clinical unit specializing in women's reproductive health, pregnancy, and childbirth care.
  • C. Department of Gynecology
    The Department of Gynecology is a specialized clinical and research unit focused on women’s reproductive health, including the diagnosis, treatment, and prevention of gynecological diseases.
  • D. 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.
  • E. Obstetrics & Gynecology
    Obstetrics & Gynecology is a leading peer-reviewed medical journal focusing on research and clinical practice in women's reproductive health and related surgical and medical specialties.
  • 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
Triple: [Faculty of Medicine, University of Ruhuna, hasDepartment, Department of Obstetrics and Gynaecology]
Generated description
The Department of Obstetrics and Gynaecology is an academic and clinical unit specializing in women’s reproductive health, pregnancy, and childbirth within the medical faculty.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Department of Obstetrics and Gynaecology
Target entity description: The Department of Obstetrics and Gynaecology is an academic and clinical unit specializing in women’s reproductive health, pregnancy, and childbirth within the medical faculty.
  • A. Department of Obstetrics and Gynaecology chosen
    The Department of Obstetrics and Gynaecology is a clinical academic unit specializing in women’s reproductive health, pregnancy, and childbirth within the Chinese University of Hong Kong’s medical faculty.
  • B. Department of Obstetrics and Gynecology
    The Department of Obstetrics and Gynecology is a medical academic and clinical unit specializing in women's reproductive health, pregnancy, and childbirth care.
  • C. Department of Gynecology
    The Department of Gynecology is a specialized clinical and research unit focused on women’s reproductive health, including the diagnosis, treatment, and prevention of gynecological diseases.
  • D. 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.
  • E. Obstetrics & Gynecology
    Obstetrics & Gynecology is a leading peer-reviewed medical journal focusing on research and clinical practice in women's reproductive health and related surgical and medical specialties.
  • F. None of above.

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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafd7ad9481908fe1d7ffcf8fab71 completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d9eaff881909a3cd9e88bb4ec5e completed May 3, 2026, 2:37 p.m.
NEDg Description generation batch_69f75e7d8970819092116ae7a769ac21 completed May 3, 2026, 2:41 p.m.
NED2 Entity disambiguation (via description) batch_69f75f35c6008190b88e14feddb93a1d completed May 3, 2026, 2:44 p.m.
Created at: April 9, 2026, 9:45 p.m.