Triple
T7974443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hunan University |
E185408
|
entity |
| Predicate | hasFaculty |
P141
|
FINISHED |
| Object |
School of Computer Science and Electronic Engineering
The School of Computer Science and Electronic Engineering is an academic unit of Hunan University specializing in education and research in computing and electronic engineering disciplines.
|
E702990
|
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: School of Computer Science and Electronic Engineering | Statement: [Hunan University, hasFaculty, School of Computer Science and Electronic Engineering]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: School of Computer Science and Electronic Engineering Context triple: [Hunan University, hasFaculty, School of Computer Science and Electronic Engineering]
-
A.
School of Computer Science and Engineering
The School of Computer Science and Engineering is a leading academic unit at the Hebrew University of Jerusalem specializing in education and research in computer science, software, and related engineering disciplines.
-
B.
School of Computer Science and Engineering
The School of Computer Science and Engineering is a major academic unit of South China University of Technology specializing in education and research in computer science, software, and related engineering fields.
-
C.
School of Electronics, Electrical Engineering and Computer Science
The School of Electronics, Electrical Engineering and Computer Science is a specialist academic unit at Queen’s University Belfast focused on teaching and research in electronic engineering, electrical engineering, and computing disciplines.
-
D.
School of Electrical Engineering and Computer Science
The School of Electrical Engineering and Computer Science is a major academic division of KTH Royal Institute of Technology in Stockholm, focusing on education and research in electrical engineering, computer science, and related technologies.
-
E.
School of Electronics and Computer Science
The School of Electronics and Computer Science is a leading academic department at the University of Southampton renowned for its research and teaching in electronics, computer science, and related technologies.
- 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: School of Computer Science and Electronic Engineering Triple: [Hunan University, hasFaculty, School of Computer Science and Electronic Engineering]
Generated description
The School of Computer Science and Electronic Engineering is an academic unit of Hunan University specializing in education and research in computing and electronic engineering disciplines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: School of Computer Science and Electronic Engineering Target entity description: The School of Computer Science and Electronic Engineering is an academic unit of Hunan University specializing in education and research in computing and electronic engineering disciplines.
-
A.
School of Computer Science and Engineering
The School of Computer Science and Engineering is a leading academic unit at the Hebrew University of Jerusalem specializing in education and research in computer science, software, and related engineering disciplines.
-
B.
School of Computer Science and Engineering
The School of Computer Science and Engineering is a major academic unit of South China University of Technology specializing in education and research in computer science, software, and related engineering fields.
-
C.
School of Electronics, Electrical Engineering and Computer Science
The School of Electronics, Electrical Engineering and Computer Science is a specialist academic unit at Queen’s University Belfast focused on teaching and research in electronic engineering, electrical engineering, and computing disciplines.
-
D.
School of Electrical Engineering and Computer Science
The School of Electrical Engineering and Computer Science is a major academic division of KTH Royal Institute of Technology in Stockholm, focusing on education and research in electrical engineering, computer science, and related technologies.
-
E.
School of Electronics and Computer Science
The School of Electronics and Computer Science is a leading academic department at the University of Southampton renowned for its research and teaching in electronics, computer science, and related technologies.
- 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_69ca829851908190b4e03829353ee7c3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bf42a508190bb661fce34ec0151 |
completed | March 31, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe0bb089881909d3ec17a3330ce25 |
completed | March 31, 2026, 2:56 p.m. |
| NEDg | Description generation | batch_69cbe43d29f8819080f7d729c4f28c75 |
completed | March 31, 2026, 3:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc32e2e1c48190b86218bff9af99f5 |
completed | March 31, 2026, 8:47 p.m. |
Created at: March 30, 2026, 5:14 p.m.