Triple
T512623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lancaster University |
E10638
|
entity |
| Predicate | hasDepartment |
P35
|
FINISHED |
| Object |
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.
|
E64084
|
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 Engineering, Lancaster University | Statement: [Lancaster University, hasDepartment, Department of Engineering, Lancaster University]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Engineering, Lancaster University Context triple: [Lancaster University, hasDepartment, Department of Engineering, Lancaster University]
-
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 Computing and Communications, Lancaster University
The School of Computing and Communications at Lancaster University is an academic department specializing in computer science, communications systems, and related digital technologies, offering teaching and research in these areas.
-
C.
Department of Physics, Lancaster University
The Department of Physics at Lancaster University is a leading UK physics department known for its research in areas such as condensed matter physics, particle physics, and cosmology, alongside strong undergraduate and postgraduate teaching programs.
-
D.
Cambridge Engineering Design Centre
The Cambridge Engineering Design Centre is a research and teaching centre at the University of Cambridge focused on advancing engineering design methods, tools, and practice across academia and industry.
-
E.
Department of Chemistry, Lancaster University
The Department of Chemistry at Lancaster University is an academic unit focused on teaching and research in chemical sciences within the university’s Faculty of Science and Technology.
- 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 Engineering, Lancaster University Triple: [Lancaster University, hasDepartment, Department of Engineering, Lancaster University]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Engineering, Lancaster University Target entity description: 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.
-
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 Computing and Communications, Lancaster University
The School of Computing and Communications at Lancaster University is an academic department specializing in computer science, communications systems, and related digital technologies, offering teaching and research in these areas.
-
C.
Department of Physics, Lancaster University
The Department of Physics at Lancaster University is a leading UK physics department known for its research in areas such as condensed matter physics, particle physics, and cosmology, alongside strong undergraduate and postgraduate teaching programs.
-
D.
Cambridge Engineering Design Centre
The Cambridge Engineering Design Centre is a research and teaching centre at the University of Cambridge focused on advancing engineering design methods, tools, and practice across academia and industry.
-
E.
Department of Chemistry, Lancaster University
The Department of Chemistry at Lancaster University is an academic unit focused on teaching and research in chemical sciences within the university’s Faculty of Science and Technology.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1804e908190a1d34ac952e84a3f |
completed | Feb. 28, 2026, 1:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4a14e37208190b4df8e75b6fe03fb |
completed | March 1, 2026, 8:27 p.m. |
| NEDg | Description generation | batch_69a4a1d418d48190b69a8dc3f3554afc |
completed | March 1, 2026, 8:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a4a27329fc8190aeb227266396c1a7 |
completed | March 1, 2026, 8:32 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.