Triple

T10314151
Position Surface form Disambiguated ID Type / Status
Subject Paul Winfield E241970 entity
Predicate awardNominationFor P10684 FINISHED
Object Sounder E659779 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: Sounder | Statement: [Paul Winfield, awardNominationFor, Sounder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sounder
Context triple: [Paul Winfield, awardNominationFor, Sounder]
  • A. Sounder
    Sounder is a regional commuter rail service in the Seattle metropolitan area operated by Sound Transit, providing weekday passenger trains primarily between Seattle, Tacoma, and Everett.
  • B. Sounder chosen
    Sounder is a 1972 American drama film about an African American sharecropping family in the Great Depression, acclaimed for its powerful storytelling and performances.
  • C. The Learning Tree
    The Learning Tree is a semi-autobiographical novel by Gordon Parks that portrays an African American boy’s coming-of-age in 1920s Kansas amid racism and moral conflict.
  • D. Sula
    Sula is a 1973 novel by American author Toni Morrison that explores Black female friendship, community, and identity in a small Ohio town.
  • E. Sula
    Sula is a coastal municipality in Møre og Romsdal county, Norway, known for its fishing industry, maritime heritage, and scenic island landscapes.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d35b7c688190b68613f28b5511bc completed April 7, 2026, 9:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7502f7b308190aaefd62f2f8a0ac3 completed April 9, 2026, 7:07 a.m.
Created at: April 6, 2026, 11:48 a.m.