Triple

T14492975
Position Surface form Disambiguated ID Type / Status
Subject Russell Offices E359411 entity
Predicate hasPart P35 FINISHED
Object R8 building
The R8 building is a component facility within the Russell Offices complex, a major Australian Defence Department administrative and command precinct in Canberra.
 E1102111 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: R8 building | Statement: [Russell Offices, hasPart, R8 building]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: R8 building
Context triple: [Russell Offices, hasPart, R8 building]
  • A. R7 building
    The R7 building is a government office block in Oslo that forms part of Norway’s central Government Quarter complex.
  • B. R5 building
    The R5 building is a key Norwegian government office complex in Oslo that houses several central ministries and administrative functions.
  • C. R4 building
    The R4 building is a government office block in Oslo that forms part of Norway's central Government Quarter complex.
  • D. R8
    R8 is a commuter rail line in the Rodalies de Catalunya network that connects various towns in the Barcelona metropolitan area without passing through the city center.
  • E. R8
    The Audi R8 is a high-performance mid-engine sports car known for its powerful engines, quattro all-wheel drive, and use of advanced lightweight construction.
  • 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: R8 building
Triple: [Russell Offices, hasPart, R8 building]
Generated description
The R8 building is a component facility within the Russell Offices complex, a major Australian Defence Department administrative and command precinct in Canberra.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: R8 building
Target entity description: The R8 building is a component facility within the Russell Offices complex, a major Australian Defence Department administrative and command precinct in Canberra.
  • A. R7 building
    The R7 building is a government office block in Oslo that forms part of Norway’s central Government Quarter complex.
  • B. R5 building
    The R5 building is a key Norwegian government office complex in Oslo that houses several central ministries and administrative functions.
  • C. R4 building
    The R4 building is a government office block in Oslo that forms part of Norway's central Government Quarter complex.
  • D. R8
    The Audi R8 is a high-performance mid-engine sports car known for its powerful engines, quattro all-wheel drive, and use of advanced lightweight construction.
  • E. R8
    R8 is a commuter rail line in the Rodalies de Catalunya network that connects various towns in the Barcelona metropolitan area without passing through the city center.
  • 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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de930f34d08190b4b30e54e2f702ed completed April 14, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d9544cc81908105554f212a9b8c completed May 8, 2026, 4:59 a.m.
NEDg Description generation batch_69fd6e75155081908cec8cac1101c17e completed May 8, 2026, 5:02 a.m.
NED2 Entity disambiguation (via description) batch_69fd6f38ea788190a957419ca1971b15 completed May 8, 2026, 5:06 a.m.
Created at: April 10, 2026, 1:20 a.m.