Triple

T3606422
Position Surface form Disambiguated ID Type / Status
Subject Roger Stevens Building E76382 entity
Predicate namedAfter P63 FINISHED
Object Roger Stevens E229411 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: Roger Stevens | Statement: [Roger Stevens Building, namedAfter, Roger Stevens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roger Stevens
Context triple: [Roger Stevens Building, namedAfter, Roger Stevens]
  • A. Roger Stevens chosen
    Roger Stevens was a prominent British civil servant and diplomat who notably served as the first Vice-Chancellor of the University of Leeds.
  • B. Don Stevens
    Don Stevens is a notable individual recognized for achievements significant enough to be distinguished from others sharing the surname Stevens.
  • C. Mark Stevens
    Mark Stevens was an American film and television actor best known for his roles in 1940s and 1950s dramas and film noir.
  • D. Mark Stevens
    Mark Stevens is a music producer known for his work with the artist Chaka.
  • E. Hal Stevens
    Hal Stevens is an individual notable enough to be recognized as a bearer of the surname Stevens, though specific widely known achievements or roles are not clearly documented.
  • 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_69ad85d93dcc819094fba90cf70f4996 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc1e33cfc8190afc716b19480fbce completed March 8, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5120849188190bea912ed14f90bf3 completed March 14, 2026, 7:45 a.m.
Created at: March 8, 2026, 3:22 p.m.