Triple

T24631690
Position Surface form Disambiguated ID Type / Status
Subject Royal College of Anaesthetists E609691 entity
Predicate hasSpecialtyFaculty P141 FINISHED
Object Faculty of Pain Medicine
The Faculty of Pain Medicine is a professional body in the UK that sets standards, training, and guidance for doctors specializing in pain medicine.
 E1645630 NE FINISHED

How this triple was built (3 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: Faculty of Pain Medicine | Statement: [Royal College of Anaesthetists, hasSpecialtyFaculty, Faculty of Pain Medicine]
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: Faculty of Pain Medicine
Triple: [Royal College of Anaesthetists, hasSpecialtyFaculty, Faculty of Pain Medicine]
Generated description
The Faculty of Pain Medicine is a professional body in the UK that sets standards, training, and guidance for doctors specializing in pain medicine.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasSpecialtyFaculty
Context triple: [Royal College of Anaesthetists, hasSpecialtyFaculty, Faculty of Pain Medicine]
  • A. hasSpecialty
    Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
  • B. hasFacultyIn
    Indicates that an institution or organization has faculty members associated with or working in a particular department, field, or academic unit.
  • C. hasFaculty chosen
    Indicates that an institution or department possesses or is associated with one or more faculty members.
  • D. hasSpecialist
    Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
  • E. hasFacultyType
    Indicates that a faculty member or academic unit is associated with a specific category or type of faculty (e.g., full-time, adjunct, visiting).
  • F. None of above.

Provenance (6 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_69e2c4d1d3708190a0f2dc6a3a8523bb completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f2be064ff88190b5d9e5ec75a41242 completed April 30, 2026, 2:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a100489a6408190b544f96761c4d1f2 completed May 22, 2026, 7:23 a.m.
NEDg Description generation batch_6a10096a949c8190a5367eb6d2fd2c4f completed May 22, 2026, 7:44 a.m.
NED2 Entity disambiguation (via description) batch_6a1009d311b08190acf35a3ed552b9c1 completed May 22, 2026, 7:46 a.m.
PD Predicate disambiguation batch_69f2a6d0ab708190b2e3b94dd20ca76b completed April 30, 2026, 12:48 a.m.
Created at: April 18, 2026, 2:32 a.m.