Triple

T18944588
Position Surface form Disambiguated ID Type / Status
Subject Neil Ferguson E463477 entity
Predicate memberOf P10 FINISHED
Object Imperial College COVID-19 Response Team
The Imperial College COVID-19 Response Team is a leading epidemiological research group whose modeling and analysis of the COVID-19 pandemic significantly influenced public health policies worldwide.
E1350610 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: Imperial College COVID-19 Response Team | Statement: [Neil Ferguson, memberOf, Imperial College COVID-19 Response Team]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Imperial College COVID-19 Response Team
Context triple: [Neil Ferguson, memberOf, Imperial College COVID-19 Response Team]
  • A. Centre for Pandemic Modelling
    The Centre for Pandemic Modelling is a research unit within Norway’s public health system that develops and applies mathematical models to understand, predict, and inform responses to infectious disease outbreaks and pandemics.
  • B. UK Parliament committees on COVID-19 response
    The UK Parliament committees on COVID-19 response are cross-party groups of MPs and peers that scrutinised the government’s handling of the coronavirus pandemic through inquiries, evidence sessions, and reports.
  • C. Management of the COVID-19 pandemic in Northern Ireland
    Management of the COVID-19 pandemic in Northern Ireland refers to the policies, public health measures, and governmental response implemented to control the spread and impact of COVID-19 within Northern Ireland.
  • D. Centre for Pandemic Preparedness
    The Centre for Pandemic Preparedness is a specialized unit within Norway’s public health system focused on strengthening surveillance, research, and response capabilities for future infectious disease outbreaks.
  • E. Centre for Emergency Infectious Diseases
    The Centre for Emergency Infectious Diseases is a specialized unit within Norway’s public health system that focuses on preparedness, surveillance, and response to serious infectious disease threats and outbreaks.
  • 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: Imperial College COVID-19 Response Team
Triple: [Neil Ferguson, memberOf, Imperial College COVID-19 Response Team]
Generated description
The Imperial College COVID-19 Response Team is a leading epidemiological research group whose modeling and analysis of the COVID-19 pandemic significantly influenced public health policies worldwide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Imperial College COVID-19 Response Team
Target entity description: The Imperial College COVID-19 Response Team is a leading epidemiological research group whose modeling and analysis of the COVID-19 pandemic significantly influenced public health policies worldwide.
  • A. Centre for Pandemic Modelling
    The Centre for Pandemic Modelling is a research unit within Norway’s public health system that develops and applies mathematical models to understand, predict, and inform responses to infectious disease outbreaks and pandemics.
  • B. UK Parliament committees on COVID-19 response
    The UK Parliament committees on COVID-19 response are cross-party groups of MPs and peers that scrutinised the government’s handling of the coronavirus pandemic through inquiries, evidence sessions, and reports.
  • C. Management of the COVID-19 pandemic in Northern Ireland
    Management of the COVID-19 pandemic in Northern Ireland refers to the policies, public health measures, and governmental response implemented to control the spread and impact of COVID-19 within Northern Ireland.
  • D. Centre for Pandemic Preparedness
    The Centre for Pandemic Preparedness is a specialized unit within Norway’s public health system focused on strengthening surveillance, research, and response capabilities for future infectious disease outbreaks.
  • E. Centre for Emergency Infectious Diseases
    The Centre for Emergency Infectious Diseases is a specialized unit within Norway’s public health system that focuses on preparedness, surveillance, and response to serious infectious disease threats and outbreaks.
  • 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_69d8dcfec90481909e926be9767e5779 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d53e6e0c81908a547e21c4819bac completed April 20, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a059fc93e0c81908cc4b9755036ea29 completed May 14, 2026, 10:11 a.m.
NEDg Description generation batch_6a05a1b640488190934aa468b3638841 completed May 14, 2026, 10:19 a.m.
NED2 Entity disambiguation (via description) batch_6a05a21b8a7c81909ad3f4148842e4c1 completed May 14, 2026, 10:21 a.m.
Created at: April 10, 2026, 11:59 a.m.