Triple

T7342303
Position Surface form Disambiguated ID Type / Status
Subject Scott Norwood E169283 entity
Predicate givenName P17 FINISHED
Object Scott E16784 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: Scott | Statement: [Scott Norwood, givenName, Scott]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scott
Context triple: [Scott Norwood, givenName, Scott]
  • A. Scott chosen
    Scott is the middle name of Francis Scott Key, the American lawyer and poet who wrote the lyrics to the United States national anthem, "The Star-Spangled Banner."
  • B. Scott
    Scott is a central fictional character in Don DeLillo’s novel "Mao II," around whom key themes of identity, terrorism, and the role of the writer in contemporary society revolve.
  • C. Scott
    Scott is a common English-language surname borne by numerous notable individuals across fields such as literature, politics, science, and entertainment.
  • D. Kay
    Kay is a common diminutive or nickname for the given name Catherine.
  • E. Blaine
    Blaine is the laid-back, surfing-obsessed teenage protagonist of the 1993 comedy film "Airborne," known for his inline skating skills and culture clash after moving from California to Cincinnati.
  • 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_69c68a57710481909f0c1f3c6ebdb6f2 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f0db2db8819088c4bed5d65571f6 completed March 27, 2026, 9:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa867b7881908590ca1ea195b1b5 completed March 28, 2026, 3:57 p.m.
Created at: March 27, 2026, 3:04 p.m.