Triple

T9084863
Position Surface form Disambiguated ID Type / Status
Subject Sir John Kingman E217725 entity
Predicate notableWork P4 FINISHED
Object Poisson processes E559807 NE FINISHED

How this triple was built (2 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: Poisson processes | Statement: [Sir John Kingman, notableWork, Poisson processes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Poisson processes
Context triple: [Sir John Kingman, notableWork, Poisson processes]
  • A. Poisson process chosen
    The Poisson process is a fundamental stochastic process in probability theory that models random events occurring independently over time or space at a constant average rate.
  • B. Stochastic Processes
    "Stochastic Processes" is a foundational textbook by Emanuel Parzen that rigorously introduces the theory and applications of random processes in probability and statistics.
  • C. Markov processes
    Markov processes are stochastic processes in which the future evolution depends only on the present state and not on the past history.
  • D. Poisson
    Poisson is a French surname most famously associated with Siméon Denis Poisson, a prominent 19th-century mathematician and physicist known for major contributions to probability theory and mathematical physics.
  • E. Khinchin–Pollaczek formula
    The Khinchin–Pollaczek formula is a result in probability theory and queueing theory that provides an explicit expression for the stationary waiting-time distribution in certain single-server queues.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca83d7a0388190ba1af89ed7ba36f9 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc960d0b008190b0e9e61fac45101d completed April 1, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffe38f0048190a9fb15e73d9bcd50 completed April 3, 2026, 5:51 p.m.
Created at: March 30, 2026, 7:13 p.m.