Triple

T10325754
Position Surface form Disambiguated ID Type / Status
Subject Girlboss E242756 entity
Predicate basedOn P98 FINISHED
Object #GIRLBOSS E242756 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: #GIRLBOSS | Statement: [Girlboss, basedOn, #GIRLBOSS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: #GIRLBOSS
Context triple: [Girlboss, basedOn, #GIRLBOSS]
  • A. Girlboss chosen
    Girlboss is a Netflix comedy-drama series loosely based on the life and business journey of Nasty Gal founder Sophia Amoruso.
  • B. She's the Boss
    "She's the Boss" is Mick Jagger's debut solo studio album, released in 1985 and showcasing his work outside of The Rolling Stones.
  • C. Like a Boss
    "Like a Boss" is a popular comedic rap song and digital short by The Lonely Island that parodies corporate culture through absurd, escalating scenarios.
  • D. Lady Boss
    Lady Boss is a bestselling novel by Jackie Collins that continues her glamorous, scandal-filled tales of power, sex, and intrigue in Hollywood.
  • E. Support the Girls
    Support the Girls is a 2018 indie comedy-drama film that follows the overworked manager of a roadside sports bar as she navigates a chaotic day supporting her staff and customers.
  • 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d7cd76348190b93562112300acfc completed April 7, 2026, 10:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71da93b988190ad568b0677b5d344 completed April 9, 2026, 3:31 a.m.
Created at: April 6, 2026, 11:51 a.m.