Triple

T7494932
Position Surface form Disambiguated ID Type / Status
Subject Edith Nourse Rogers E177098 entity
Predicate familyName P18 FINISHED
Object Rogers E773 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: Rogers | Statement: [Edith Nourse Rogers, familyName, Rogers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rogers
Context triple: [Edith Nourse Rogers, familyName, Rogers]
  • A. Rogers
    Rogers is a growing city in northwestern Arkansas known for its role in the Fayetteville–Springdale–Rogers metropolitan area and as a regional commercial and retail hub.
  • B. Rogers
    Rogers is a small suburban city in Minnesota known for its location northwest of Minneapolis and its blend of residential neighborhoods, light industry, and retail development.
  • C. Rogers chosen
    Rogers is a common English-language surname borne by numerous notable individuals across fields such as science, politics, entertainment, and sports.
  • D. Rogers
    Rogers is a major Canadian communications and media company known for its wireless, cable, internet, and sports media services.
  • E. Rogers & Wells
    Rogers & Wells was a prominent New York-based law firm known for its corporate and international legal practice before merging into Clifford Chance in 2000.
  • 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_69c69f2583808190bd1a4936c42a5815 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f57b5b4c8190ab839e6a98ee86ed completed March 27, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c819f00819087fef27e4f4fdc1c completed March 28, 2026, 8:39 p.m.
Created at: March 27, 2026, 3:43 p.m.