Triple

T9530279
Position Surface form Disambiguated ID Type / Status
Subject RusLine E229872 entity
Predicate IATAcode P418 FINISHED
Object 7R
7R is the IATA airline designator assigned to RusLine, a regional airline based in Russia.
 E804996 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: 7R | Statement: [RusLine, IATAcode, 7R]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 7R
Context triple: [RusLine, IATAcode, 7R]
  • A. R5
    R5 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • B. R5
    R5 is the U.S. Forest Service’s Pacific Southwest Region, which oversees national forests primarily in California and parts of neighboring areas.
  • C. R5
    R5 was a former designation for a commuter rail line in the SEPTA Regional Rail system serving the Paoli/Thorndale corridor in the Philadelphia area.
  • D. R
    R is a New York City Subway service that runs along the Broadway Line in Manhattan and Queens, providing local transit through key commercial and residential areas.
  • E. R
    R is a widely used open-source programming language and environment focused on statistical computing, data analysis, and graphical visualization.
  • 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: 7R
Triple: [RusLine, IATAcode, 7R]
Generated description
7R is the IATA airline designator assigned to RusLine, a regional airline based in Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 7R
Target entity description: 7R is the IATA airline designator assigned to RusLine, a regional airline based in Russia.
  • A. R5
    R5 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • B. R5
    R5 was a former designation for a commuter rail line in the SEPTA Regional Rail system serving the Paoli/Thorndale corridor in the Philadelphia area.
  • C. R5
    R5 is the U.S. Forest Service’s Pacific Southwest Region, which oversees national forests primarily in California and parts of neighboring areas.
  • D. R
    R is a New York City Subway service that runs along the Broadway Line in Manhattan and Queens, providing local transit through key commercial and residential areas.
  • E. R
    R is a widely used open-source programming language and environment focused on statistical computing, data analysis, and graphical visualization.
  • 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_69ca8479934c81908006d0e6e970ae05 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98b2de3081909be70d9ab187dce6 completed April 1, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c38a3848190ab3561f70497c9eb completed April 4, 2026, 5:36 p.m.
NEDg Description generation batch_69d14d23573c8190aeebf2fdac20a332 completed April 4, 2026, 5:40 p.m.
NED2 Entity disambiguation (via description) batch_69d14da4514481908a530b5d77ad832a completed April 4, 2026, 5:43 p.m.
Created at: March 30, 2026, 8 p.m.