Triple

T3934458
Position Surface form Disambiguated ID Type / Status
Subject Seth Rogen E90874 entity
Predicate appearedInFilm P795 FINISHED
Object 50/50 E399720 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: 50/50 | Statement: [Seth Rogen, appearedInFilm, 50/50]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 50/50
Context triple: [Seth Rogen, appearedInFilm, 50/50]
  • A. 50/50 chosen
    50/50 is a 2011 dramedy film starring Joseph Gordon-Levitt and Seth Rogen that follows a young man's emotional and humorous journey after being diagnosed with cancer.
  • B. Win Win
    Win Win is a 2011 indie dramedy film about a struggling attorney and high school wrestling coach who takes in a teenage runaway, featuring a critically acclaimed performance by Paul Giamatti.
  • C. Two of a Kind
    Two of a Kind is a 1983 romantic fantasy comedy film starring Olivia Newton-John and John Travolta, known for reuniting the Grease co-stars in a quirky, heaven-versus-earth storyline.
  • D. The Other Half
    The Other Half is a 2016 Canadian romantic drama film starring Tatiana Maslany and Tom Cullen that explores love, mental illness, and grief.
  • E. C50
    C50 is a popular model of Honda’s Super Cub series of small, fuel-efficient commuter motorcycles, known for their durability and widespread use worldwide.
  • 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_69aed95f26e0819094b0e71974543a19 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeedcbf0188190a5e828707a77752a completed March 9, 2026, 3:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5338afa348190bc5ac0b0319c6e45 completed March 14, 2026, 10:08 a.m.
Created at: March 9, 2026, 3:23 p.m.