Triple

T1178686
Position Surface form Disambiguated ID Type / Status
Subject Norman Spinrad E25086 entity
Predicate givenName P17 FINISHED
Object Norman E1119 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: Norman | Statement: [Norman Spinrad, givenName, Norman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norman
Context triple: [Norman Spinrad, givenName, Norman]
  • A. Norman
    Norman is a city in central Oklahoma known for its strong ties to meteorology and atmospheric research, including hosting major national weather institutions.
  • B. Norman
    The Normans were a medieval people of Viking origin who settled in northern France and became influential conquerors and rulers across Europe and the Mediterranean, notably shaping the culture and politics of regions such as England, southern Italy, and Sicily.
  • C. Norman chosen
    Norman is a masculine given name of English origin that became widely used in the English-speaking world.
  • D. Southery
    Southery is a village and civil parish in Norfolk, England, situated in the Fens near the River Great Ouse.
  • E. Bettany
    Bettany is an English surname most notably associated with actor Paul Bettany.
  • 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_69a494267b4c819088c97a59182bf56a completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd10ccc481908d5bcef648aab3c1 completed March 1, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6f1f1c188190a96f5718c4e7d59d completed March 7, 2026, 6:31 p.m.
Created at: March 1, 2026, 7:45 p.m.