Triple

T14574431
Position Surface form Disambiguated ID Type / Status
Subject Megan Walsh E342002 entity
Predicate appearsIn P795 FINISHED
Object Barely Lethal E46508 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: Barely Lethal | Statement: [Megan Walsh, appearsIn, Barely Lethal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barely Lethal
Context triple: [Megan Walsh, appearsIn, Barely Lethal]
  • A. Barely Lethal chosen
    Barely Lethal is a 2015 action-comedy film about a teenage assassin trying to live a normal high school life, starring Hailee Steinfeld and Samuel L. Jackson.
  • B. Hard to Kill
    Hard to Kill is a professional wrestling pay-per-view event produced annually by Impact Wrestling.
  • C. Hard to Kill
    Hard to Kill is a 1990 action film starring Steven Seagal as a detective who awakens from a coma to seek revenge against corrupt politicians and criminals who tried to kill him.
  • D. Deadlier Than the Male
    Deadlier Than the Male is a 1967 British spy thriller film featuring suave insurance investigator Bulldog Drummond battling a pair of glamorous female assassins.
  • E. Bedside Gun
    Bedside Gun is a novelty bedside lamp designed to resemble a firearm, combining functional lighting with a playful, provocative aesthetic.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb3f49d58819094fcd2a702e146cb completed April 14, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8acc788081909c41905785fa9a29 completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:24 a.m.