Triple

T7920722
Position Surface form Disambiguated ID Type / Status
Subject PDP-11 E183936 entity
Predicate hasRegister P4184 FINISHED
Object R3
R3 is one of the general-purpose registers in the PDP-11 minicomputer architecture, used for arithmetic, logical operations, and addressing.
 E697035 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: R3 | Statement: [PDP-11, hasRegister, R3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: R3
Context triple: [PDP-11, hasRegister, R3]
  • 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. R4
    R4 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • E. R37
    R37 is a regional road in South Africa that serves as a key route connecting the town of Lydenburg with other parts of the Mpumalanga and Limpopo provinces.
  • 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: R3
Triple: [PDP-11, hasRegister, R3]
Generated description
R3 is one of the general-purpose registers in the PDP-11 minicomputer architecture, used for arithmetic, logical operations, and addressing.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: R3
Target entity description: R3 is one of the general-purpose registers in the PDP-11 minicomputer architecture, used for arithmetic, logical operations, and addressing.
  • 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. R4
    R4 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • E. R37
    R37 is a regional road in South Africa that serves as a key route connecting the town of Lydenburg with other parts of the Mpumalanga and Limpopo provinces.
  • 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_69ca828efbe48190bd48482650182e79 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a9360f881908ca2433d0623315b completed March 31, 2026, 3:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5beea7988190972f7d02881d98f6 completed March 31, 2026, 5:30 a.m.
NEDg Description generation batch_69cb5f222c808190b9ef39896f149278 completed March 31, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69cb76bb9a308190a9d7b34838d696db completed March 31, 2026, 7:24 a.m.
Created at: March 30, 2026, 5:06 p.m.