Triple

T20128255
Position Surface form Disambiguated ID Type / Status
Subject Russell County E490814 entity
Predicate containsSettlement P847 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: [Russell County, containsSettlement, Russell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Russell
Context triple: [Russell County, containsSettlement, Russell]
  • A. Russell chosen
    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 a locality in Canberra, Australia, known primarily as a major government and defence precinct housing key national security and administrative offices.
  • C. 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.
  • D. Russell
    Russell is a supporting character from the classic Doctor Who serial "Attack of the Cybermen," involved in the story’s conflict with the Cybermen.
  • E. Russell
    Russell is the middle name of Scott Russell Hayes, used as part of his full personal name.
  • 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6675fe3d48190b0c20b483a951e68 completed April 20, 2026, 5:50 p.m.
Created at: April 11, 2026, 11:31 p.m.