Triple

T1386176
Position Surface form Disambiguated ID Type / Status
Subject Peter J. Denning E29850 entity
Predicate familyName P18 FINISHED
Object Denning
Denning is a surname most prominently associated with Peter J. Denning, an influential American computer scientist known for his work in operating systems and the science of computing.
 E157646 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: Denning | Statement: [Peter J. Denning, familyName, Denning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Denning
Context triple: [Peter J. Denning, familyName, Denning]
  • A. Howden
    Howden is a residential neighbourhood within the town of Livingston in West Lothian, Scotland.
  • B. Daniels
    Daniels is a common English-language surname borne by numerous notable individuals across politics, sports, entertainment, and other fields.
  • C. Darrow
    Darrow is a surname most famously associated with Clarence Darrow, the prominent American lawyer and civil libertarian known for high-profile cases in the early 20th century.
  • D. Dennis
    Dennis is a coastal town on Cape Cod in Massachusetts known for its beaches, historic charm, and popular summer tourism.
  • E. Den
    Den was a prominent pharaoh of Egypt’s First Dynasty, known for early administrative innovations and military campaigns that helped consolidate the young Egyptian state.
  • 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: Denning
Triple: [Peter J. Denning, familyName, Denning]
Generated description
Denning is a surname most prominently associated with Peter J. Denning, an influential American computer scientist known for his work in operating systems and the science of computing.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Denning
Target entity description: Denning is a surname most prominently associated with Peter J. Denning, an influential American computer scientist known for his work in operating systems and the science of computing.
  • A. Howden
    Howden is a residential neighbourhood within the town of Livingston in West Lothian, Scotland.
  • B. Daniels
    Daniels is a common English-language surname borne by numerous notable individuals across politics, sports, entertainment, and other fields.
  • C. Darrow
    Darrow is a surname most famously associated with Clarence Darrow, the prominent American lawyer and civil libertarian known for high-profile cases in the early 20th century.
  • D. Dennis
    Dennis is a coastal town on Cape Cod in Massachusetts known for its beaches, historic charm, and popular summer tourism.
  • E. Den
    Den was a prominent pharaoh of Egypt’s First Dynasty, known for early administrative innovations and military campaigns that helped consolidate the young Egyptian state.
  • 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_69a498dc92f8819094a1108f8ac90f43 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c339f3d481909c04b14129899945 completed March 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd48fc7f88190a971e6b6fa01453e completed March 8, 2026, 1:44 a.m.
NEDg Description generation batch_69acd56a42a481909b2b4efc3d3dac49 completed March 8, 2026, 1:48 a.m.
NED2 Entity disambiguation (via description) batch_69acd5d853a08190980fe79aa583390a completed March 8, 2026, 1:50 a.m.
Created at: March 1, 2026, 7:59 p.m.