Triple
T14720843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wuhan University of Technology |
E345807
|
entity |
| Predicate | hasSchool |
P113
|
FINISHED |
| Object |
School of Transportation and Logistics Engineering
The School of Transportation and Logistics Engineering is an academic unit of Wuhan University of Technology specializing in education and research on transportation systems, logistics management, and related engineering disciplines.
|
E1115564
|
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 Transportation and Logistics Engineering | Statement: [Wuhan University of Technology, hasSchool, School of Transportation and Logistics Engineering]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: School of Transportation and Logistics Engineering Context triple: [Wuhan University of Technology, hasSchool, School of Transportation and Logistics Engineering]
-
A.
School of Transportation Engineering
The School of Transportation Engineering is a specialized academic unit of Tongji University focused on education and research in transportation systems, infrastructure, and related engineering fields.
-
B.
School of Civil Engineering and Transportation
The School of Civil Engineering and Transportation is an academic unit of South China University of Technology specializing in education and research in civil engineering, transportation engineering, and related infrastructure fields.
-
C.
School of Transport and Logistics
The School of Transport and Logistics is an academic faculty of Lagos State University specializing in education and research on transportation systems, logistics management, and related infrastructure.
-
D.
Faculty of Transportation Sciences
The Faculty of Transportation Sciences is a specialized faculty of the Czech Technical University in Prague focused on education and research in transport, logistics, and related technologies.
-
E.
Faculty of Civil and Transport Engineering
The Faculty of Civil and Transport Engineering is an academic unit of Poznań University of Technology specializing in education and research in civil engineering, transportation systems, and related infrastructure 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: School of Transportation and Logistics Engineering Triple: [Wuhan University of Technology, hasSchool, School of Transportation and Logistics Engineering]
Generated description
The School of Transportation and Logistics Engineering is an academic unit of Wuhan University of Technology specializing in education and research on transportation systems, logistics management, and related engineering disciplines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: School of Transportation and Logistics Engineering Target entity description: The School of Transportation and Logistics Engineering is an academic unit of Wuhan University of Technology specializing in education and research on transportation systems, logistics management, and related engineering disciplines.
-
A.
School of Transportation Engineering
The School of Transportation Engineering is a specialized academic unit of Tongji University focused on education and research in transportation systems, infrastructure, and related engineering fields.
-
B.
School of Civil Engineering and Transportation
The School of Civil Engineering and Transportation is an academic unit of South China University of Technology specializing in education and research in civil engineering, transportation engineering, and related infrastructure fields.
-
C.
School of Transport and Logistics
The School of Transport and Logistics is an academic faculty of Lagos State University specializing in education and research on transportation systems, logistics management, and related infrastructure.
-
D.
Faculty of Transportation Sciences
The Faculty of Transportation Sciences is a specialized faculty of the Czech Technical University in Prague focused on education and research in transport, logistics, and related technologies.
-
E.
Faculty of Civil and Transport Engineering
The Faculty of Civil and Transport Engineering is an academic unit of Poznań University of Technology specializing in education and research in civil engineering, transportation systems, and related infrastructure 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec25d56fc8190871873ca55d49272 |
completed | April 14, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdf0957bb081908f1f382f3be8ec20 |
completed | May 8, 2026, 2:17 p.m. |
| NEDg | Description generation | batch_69fdf440a03c8190886119ab3c8ab610 |
completed | May 8, 2026, 2:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdf4f2acbc8190b51ee456093a2813 |
completed | May 8, 2026, 2:36 p.m. |
Created at: April 10, 2026, 1:29 a.m.