Triple

T8047605
Position Surface form Disambiguated ID Type / Status
Subject School of Civil Engineering, University of Tehran E187592 entity
Predicate hasLaboratory P105 FINISHED
Object transportation and traffic laboratory
The transportation and traffic laboratory is a research and educational facility at the University of Tehran’s School of Civil Engineering focused on studying and improving transportation systems, traffic flow, and related infrastructure.
 E706440 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: transportation and traffic laboratory | Statement: [School of Civil Engineering, University of Tehran, hasLaboratory, transportation and traffic laboratory]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: transportation and traffic laboratory
Context triple: [School of Civil Engineering, University of Tehran, hasLaboratory, transportation and traffic laboratory]
  • A. Transportation Research and Analysis Computing Center
    The Transportation Research and Analysis Computing Center is a high-performance computing facility dedicated to advanced modeling, simulation, and analysis of transportation systems and technologies.
  • B. Faculty of Transportation and Traffic Sciences
    The Faculty of Transportation and Traffic Sciences is an academic division of Dresden University of Technology specializing in research and education on transportation systems, traffic engineering, and mobility.
  • C. Roadway, Transportation and Traffic Safety Research Center
    The Roadway, Transportation and Traffic Safety Research Center is a specialized research institute focused on improving road infrastructure, transportation systems, and traffic safety through scientific studies and applied innovation.
  • D. National Transportation Research Center
    The National Transportation Research Center is a U.S. Department of Energy facility focused on advanced transportation technologies, including vehicle efficiency, emissions reduction, and sustainable mobility systems.
  • E. Texas A&M Transportation Institute
    The Texas A&M Transportation Institute is a leading research agency specializing in transportation systems, safety, and infrastructure innovation.
  • 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: transportation and traffic laboratory
Triple: [School of Civil Engineering, University of Tehran, hasLaboratory, transportation and traffic laboratory]
Generated description
The transportation and traffic laboratory is a research and educational facility at the University of Tehran’s School of Civil Engineering focused on studying and improving transportation systems, traffic flow, and related infrastructure.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: transportation and traffic laboratory
Target entity description: The transportation and traffic laboratory is a research and educational facility at the University of Tehran’s School of Civil Engineering focused on studying and improving transportation systems, traffic flow, and related infrastructure.
  • A. Transportation Research and Analysis Computing Center
    The Transportation Research and Analysis Computing Center is a high-performance computing facility dedicated to advanced modeling, simulation, and analysis of transportation systems and technologies.
  • B. Faculty of Transportation and Traffic Sciences
    The Faculty of Transportation and Traffic Sciences is an academic division of Dresden University of Technology specializing in research and education on transportation systems, traffic engineering, and mobility.
  • C. Roadway, Transportation and Traffic Safety Research Center
    The Roadway, Transportation and Traffic Safety Research Center is a specialized research institute focused on improving road infrastructure, transportation systems, and traffic safety through scientific studies and applied innovation.
  • D. National Transportation Research Center
    The National Transportation Research Center is a U.S. Department of Energy facility focused on advanced transportation technologies, including vehicle efficiency, emissions reduction, and sustainable mobility systems.
  • E. Texas A&M Transportation Institute
    The Texas A&M Transportation Institute is a leading research agency specializing in transportation systems, safety, and infrastructure innovation.
  • 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_69ca82b15e948190a62fd7af5218426a completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3f4f0bf88190b8a706186118c977 completed March 31, 2026, 3:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc5711d2bc8190911f2cade7596be5 completed March 31, 2026, 11:21 p.m.
NEDg Description generation batch_69cc58edb31881909b6efd2fbbc2480e completed March 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_69cc5ccee5648190a8ebdf8029eded98 completed March 31, 2026, 11:46 p.m.
Created at: March 30, 2026, 5:24 p.m.