Triple

T17772416
Position Surface form Disambiguated ID Type / Status
Subject John Russell, Viscount Amberley E443672 entity
Predicate familyName P18 FINISHED
Object Russell NE NERFINISHED

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: Russell | Statement: [John Russell, Viscount Amberley, familyName, Russell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Russell
Context triple: [John Russell, Viscount Amberley, familyName, Russell]
  • A. Russell
    Russell is a rural municipality in eastern Ontario, Canada, known for its bilingual (English and French) community and proximity to Ottawa.
  • B. Russell
    Russell is the enthusiastic young Wilderness Explorer who befriends elderly widower Carl Fredricksen in Pixar's animated film "Up."
  • C. Russell
    Russell is a sharp-tongued, wisecracking young member of the Junkyard Gang in the animated series "Fat Albert and the Cosby Kids."
  • D. Russell chosen
    Russell is a prominent English surname historically associated with influential aristocratic and political families in Britain.
  • E. Russell
    Russell is the middle name of Rensselaer Russell Nelson, an American jurist who served as a United States federal judge in the 19th century.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9ef17708190bdf7e2adbf14ddc2 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4871a2130819081743ae89dddc64b completed April 19, 2026, 7:41 a.m.
Created at: April 10, 2026, 10:11 a.m.