Triple

T17015626
Position Surface form Disambiguated ID Type / Status
Subject IG Patel Professor of Economics and Government E412812 entity
Predicate hostDepartment P95215 FINISHED
Object Department of Government, London School of Economics and Political Science
The Department of Government at the London School of Economics and Political Science is a leading academic department specializing in political science and public policy research and education within a globally renowned social science university.
E1246735 NE FINISHED

How this triple was built (5 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 Government, London School of Economics and Political Science | Statement: [IG Patel Professor of Economics and Government, hostDepartment, Department of Government, London School of Economics and Political Science]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Department of Government, London School of Economics and Political Science
Context triple: [IG Patel Professor of Economics and Government, hostDepartment, Department of Government, London School of Economics and Political Science]
  • A. UCL Department of Political Science
    The UCL Department of Political Science is a leading UK academic department specializing in political science, public policy, and international relations, known for its research-intensive programs and policy engagement.
  • B. Department of Politics and International Studies
    The Department of Politics and International Studies at the University of Warwick is an academic department specializing in the study and research of politics, international relations, and global affairs.
  • C. Department of Politics and International Relations, University of Oxford
    The Department of Politics and International Relations at the University of Oxford is a leading academic centre for the study and research of politics, government, and international affairs.
  • D. School of Politics and International Relations, Queen Mary University of London
    The School of Politics and International Relations at Queen Mary University of London is an academic department specializing in the study and research of politics, international relations, and related social sciences.
  • E. Department of Politics and International Studies, University of Cambridge
    The Department of Politics and International Studies at the University of Cambridge is a leading academic centre for the study and research of politics, international relations, and related social sciences.
  • 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 Government, London School of Economics and Political Science
Triple: [IG Patel Professor of Economics and Government, hostDepartment, Department of Government, London School of Economics and Political Science]
Generated description
The Department of Government at the London School of Economics and Political Science is a leading academic department specializing in political science and public policy research and education within a globally renowned social science university.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Department of Government, London School of Economics and Political Science
Target entity description: The Department of Government at the London School of Economics and Political Science is a leading academic department specializing in political science and public policy research and education within a globally renowned social science university.
  • A. UCL Department of Political Science
    The UCL Department of Political Science is a leading UK academic department specializing in political science, public policy, and international relations, known for its research-intensive programs and policy engagement.
  • B. Department of Politics and International Studies
    The Department of Politics and International Studies at the University of Warwick is an academic department specializing in the study and research of politics, international relations, and global affairs.
  • C. Department of Politics and International Relations, University of Oxford
    The Department of Politics and International Relations at the University of Oxford is a leading academic centre for the study and research of politics, government, and international affairs.
  • D. School of Politics and International Relations, Queen Mary University of London
    The School of Politics and International Relations at Queen Mary University of London is an academic department specializing in the study and research of politics, international relations, and related social sciences.
  • E. Department of Politics and International Studies, University of Cambridge
    The Department of Politics and International Studies at the University of Cambridge is a leading academic centre for the study and research of politics, international relations, and related social sciences.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hostDepartment
Context triple: [IG Patel Professor of Economics and Government, hostDepartment, Department of Government, London School of Economics and Political Science]
  • A. basedInDepartment chosen
    Indicates that an entity operates or has its primary affiliation within a specific department.
  • B. department
    Indicates that one entity functions as an organizational unit or division within another, typically larger, entity.
  • C. laterDepartment
    Indicates that one department occurs or is considered after another in a defined ordering or sequence.
  • D. propDepartment
    Indicates that one entity functions as a department or organizational subdivision associated with another entity.
  • E. departmentNumber
    Indicates the specific numeric code assigned to identify a particular department within an organization or system.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d47f198c8190b0473f638101f606 completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b4ba2a88190a49d355836ff1dcf completed May 10, 2026, 11:56 p.m.
NEDg Description generation batch_6a011d5d720c8190ba6f7146a8a5f7f4 completed May 11, 2026, 12:05 a.m.
NED2 Entity disambiguation (via description) batch_6a011dd998888190a60d3880fd5c20c2 completed May 11, 2026, 12:07 a.m.
PD Predicate disambiguation batch_69e35d5be7f48190af9db67a1e23850f completed April 18, 2026, 10:30 a.m.
Created at: April 10, 2026, 5:33 a.m.