Triple

T7717302
Position Surface form Disambiguated ID Type / Status
Subject UCL Science Library E174916 entity
Predicate primaryUserGroup P17010 FINISHED
Object Faculty of Engineering Sciences at UCL
The Faculty of Engineering Sciences at UCL is a leading academic division specializing in engineering and related disciplines, known for its research-intensive programs and innovation in science and technology.
E684875 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: Faculty of Engineering Sciences at UCL | Statement: [UCL Science Library, primaryUserGroup, Faculty of Engineering Sciences at UCL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faculty of Engineering Sciences at UCL
Context triple: [UCL Science Library, primaryUserGroup, Faculty of Engineering Sciences at UCL]
  • A. Department of Engineering, University of Cambridge
    The Department of Engineering at the University of Cambridge is one of the world’s leading engineering schools, renowned for its cutting-edge research, broad range of engineering disciplines, and rigorous undergraduate and postgraduate programs.
  • B. School of Technology, University of Cambridge
    The School of Technology at the University of Cambridge is a major academic division that oversees engineering, business, and related technology-focused departments and research centers within the university.
  • C. School of Engineering, University of Edinburgh
    The School of Engineering at the University of Edinburgh is a major academic unit offering research-led education and innovation across multiple engineering disciplines within one of Scotland’s leading universities.
  • D. Department of Engineering, Lancaster University
    The Department of Engineering at Lancaster University is a multidisciplinary engineering school known for its research and teaching in areas such as mechanical, electronic, chemical, and nuclear engineering.
  • E. Faculty of Engineering and Physical Sciences at Queen’s University Belfast
    The Faculty of Engineering and Physical Sciences at Queen’s University Belfast is an academic division that encompasses disciplines such as engineering, computing, and the physical sciences, supporting research and teaching across these technical fields.
  • 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: Faculty of Engineering Sciences at UCL
Triple: [UCL Science Library, primaryUserGroup, Faculty of Engineering Sciences at UCL]
Generated description
The Faculty of Engineering Sciences at UCL is a leading academic division specializing in engineering and related disciplines, known for its research-intensive programs and innovation in science and technology.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Faculty of Engineering Sciences at UCL
Target entity description: The Faculty of Engineering Sciences at UCL is a leading academic division specializing in engineering and related disciplines, known for its research-intensive programs and innovation in science and technology.
  • A. Department of Engineering, University of Cambridge
    The Department of Engineering at the University of Cambridge is one of the world’s leading engineering schools, renowned for its cutting-edge research, broad range of engineering disciplines, and rigorous undergraduate and postgraduate programs.
  • B. School of Technology, University of Cambridge
    The School of Technology at the University of Cambridge is a major academic division that oversees engineering, business, and related technology-focused departments and research centers within the university.
  • C. School of Engineering, University of Edinburgh
    The School of Engineering at the University of Edinburgh is a major academic unit offering research-led education and innovation across multiple engineering disciplines within one of Scotland’s leading universities.
  • D. Department of Engineering, Lancaster University
    The Department of Engineering at Lancaster University is a multidisciplinary engineering school known for its research and teaching in areas such as mechanical, electronic, chemical, and nuclear engineering.
  • E. Faculty of Engineering and Physical Sciences at Queen’s University Belfast
    The Faculty of Engineering and Physical Sciences at Queen’s University Belfast is an academic division that encompasses disciplines such as engineering, computing, and the physical sciences, supporting research and teaching across these technical fields.
  • 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_69c6995c463c8190a14458036249d419 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c702ceb23481909600f876023dde92 completed March 27, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b50cf3208190af9bb2d4126d381b completed March 29, 2026, 5:13 a.m.
NEDg Description generation batch_69c8b7d8b4b081908f8739a91e96e6ec completed March 29, 2026, 5:25 a.m.
NED2 Entity disambiguation (via description) batch_69c8b845194c8190b65257cc02b09e6c completed March 29, 2026, 5:27 a.m.
Created at: March 27, 2026, 4:05 p.m.