Triple

T6642445
Position Surface form Disambiguated ID Type / Status
Subject Lydenburg E150617 entity
Predicate roadConnection P385 FINISHED
Object R540
R540 is a regional road in South Africa that serves as a connector route in the Mpumalanga province, linking towns such as Lydenburg to surrounding areas.
 E609438 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: R540 | Statement: [Lydenburg, roadConnection, R540]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: R540
Context triple: [Lydenburg, roadConnection, R540]
  • A. R55
    R55 is a regional road in South Africa that runs through Gauteng, connecting areas such as Midrand with surrounding suburbs and major routes.
  • 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 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • D. R-4
    The R-4 is a World War II–era Sikorsky helicopter recognized as the first mass-produced helicopter and the first to be used operationally by the U.S. military.
  • E. R-46
    R-46 is a class of New York City Subway rolling stock built in the 1970s for the IND/BMT divisions and known for its stainless-steel body and long service life.
  • 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: R540
Triple: [Lydenburg, roadConnection, R540]
Generated description
R540 is a regional road in South Africa that serves as a connector route in the Mpumalanga province, linking towns such as Lydenburg to surrounding areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: R540
Target entity description: R540 is a regional road in South Africa that serves as a connector route in the Mpumalanga province, linking towns such as Lydenburg to surrounding areas.
  • A. R55
    R55 is a regional road in South Africa that runs through Gauteng, connecting areas such as Midrand with surrounding suburbs and major routes.
  • 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 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • D. R-4
    The R-4 is a World War II–era Sikorsky helicopter recognized as the first mass-produced helicopter and the first to be used operationally by the U.S. military.
  • E. R-46
    R-46 is a class of New York City Subway rolling stock built in the 1970s for the IND/BMT divisions and known for its stainless-steel body and long service life.
  • 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_69c687f1a3048190828b7342f7125d5c completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aff5da8881909a512c1c82eb882a completed March 27, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eeef3f7481909929838858225f41 completed March 27, 2026, 8:56 p.m.
NEDg Description generation batch_69c6f0a1149c8190af55a613eada84b6 completed March 27, 2026, 9:03 p.m.
NED2 Entity disambiguation (via description) batch_69c6f17ccd7c8190918e03b114f4f064 completed March 27, 2026, 9:07 p.m.
Created at: March 27, 2026, 2 p.m.