Triple

T14430781
Position Surface form Disambiguated ID Type / Status
Subject Michael Chernus E357820 entity
Predicate notableWork P4 FINISHED
Object Paterson E592799 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: Paterson | Statement: [Michael Chernus, notableWork, Paterson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paterson
Context triple: [Michael Chernus, notableWork, Paterson]
  • A. Paterson chosen
    Paterson is a 2016 independent drama film that quietly follows a week in the life of a bus driver-poet in New Jersey, reflecting on routine, creativity, and everyday beauty.
  • B. Paterson
    Paterson is a long, modernist epic poem by William Carlos Williams that explores the life, landscape, and history of the city of Paterson, New Jersey.
  • C. Paterson
    Paterson is an Australian federal electoral division in New South Wales, represented in the national Parliament.
  • D. Paterson
    Paterson is a Scottish-origin surname borne by various notable individuals across politics, law, sports, and the arts.
  • E. Paterson
    Paterson is a town in South Africa’s Eastern Cape province, known as a small rural settlement and gateway to nearby game reserves and agricultural areas.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de914570f08190b1c7c1c57a0cb476 completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d84fd888190b05dcf9191bae337 completed May 8, 2026, 4:58 a.m.
Created at: April 10, 2026, 1:18 a.m.