Triple

T11437336
Position Surface form Disambiguated ID Type / Status
Subject Salvation E271042 entity
Predicate relatedWork P37 FINISHED
Object Riches E429337 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: Riches | Statement: [Salvation, relatedWork, Riches]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Riches
Context triple: [Salvation, relatedWork, Riches]
  • A. Lord of Wealth
    Lord of Wealth is an epithet of Kubera, the Hindu god associated with riches, prosperity, and the guardianship of treasure.
  • B. The Riches chosen
    The Riches is a darkly comedic American television drama series about a family of Irish Traveller con artists who assume the identities of a wealthy suburban couple.
  • C. That Fortune
    "That Fortune" is a lesser-known novel by American essayist and editor Charles Dudley Warner, reflecting his characteristic blend of social observation and genteel humor.
  • D. Reiche
    Reiche is a German surname most notably associated with Maria Reiche, the mathematician and archaeologist famed for her work on the Nazca Lines in Peru.
  • E. The Millionaire
    The Millionaire is a 1931 American pre-Code comedy film starring George Arliss as a retired businessman who secretly returns to work, produced by Warner Bros. and associated with filmmaker Bryan Foy.
  • 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_69d6aadeef688190874bcecd88b3dd9b completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8088711ec8190afae9f4d9f2a11ca completed April 9, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d38727fc8190b5daac83e03491e6 completed April 20, 2026, 7:19 a.m.
Created at: April 8, 2026, 9:35 p.m.