Triple

T3175456
Position Surface form Disambiguated ID Type / Status
Subject Good Morning (musical number) E66454 entity
Predicate featuresCharacter P626 FINISHED
Object Kathy Selden E66043 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: Kathy Selden | Statement: [Good Morning (musical number), featuresCharacter, Kathy Selden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kathy Selden
Context triple: [Good Morning (musical number), featuresCharacter, Kathy Selden]
  • A. Kathy Selden chosen
    Kathy Selden is the aspiring actress and love interest in the classic Hollywood musical film "Singin' in the Rain."
  • B. Lenore Blum
    Lenore Blum is an American mathematician and computer scientist known for her work in complexity theory, real computation, and advocacy for women in STEM.
  • C. Alice Robertson
    Alice Robertson is known as the former wife of Apple co-founder and engineer Steve Wozniak.
  • D. Laura Ricketts
    Laura Ricketts is an American attorney, co-owner of the Chicago Cubs, and prominent LGBTQ+ activist and political donor.
  • E. Cathy A. Sandeen
    Cathy A. Sandeen is an American academic leader and administrator known for serving as president of multiple public universities in the United States.
  • 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_69ad8586a34c8190944c63ec11a8de1a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada671e6848190a683eec1519b9268 completed March 8, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b235f16e60819091cbdb76130ecc40 completed March 12, 2026, 3:41 a.m.
Created at: March 8, 2026, 3:06 p.m.