Triple

T16284255
Position Surface form Disambiguated ID Type / Status
Subject Lashana Lynch E395347 entity
Predicate notableWork P4 FINISHED
Object Fast Girls E1010627 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: Fast Girls | Statement: [Lashana Lynch, notableWork, Fast Girls]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fast Girls
Context triple: [Lashana Lynch, notableWork, Fast Girls]
  • A. Fast Girls
    Fast Girls is a song by the American boy band Dream Street, featured as one of the tracks on their releases.
  • B. Fast Girls chosen
    Fast Girls is a 2012 British sports drama film about rival female sprinters competing for relay glory, co-written by and co-starring Noel Clarke.
  • C. Fast Life
    "Fast Life" is a hip-hop track by American rapper Paul Wall that showcases his signature Southern rap style and themes of hustle and street luxury.
  • D. Light Girls
    Light Girls is a documentary film that explores the experiences, challenges, and cultural perceptions surrounding light-skinned Black women.
  • E. The Fast Lady
    The Fast Lady is a 1962 British comedy film about an enthusiastic young man, his beloved sports car, and the romantic and social scrapes that ensue.
  • 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24912c5808190a0d9c9f491315068 completed April 17, 2026, 2:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017c8f51c8190b73cdf2834eda57f completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:05 a.m.