Triple

T22555783
Position Surface form Disambiguated ID Type / Status
Subject Rachel Jansen E557677 entity
Predicate createdBy P806 FINISHED
Object Jason Segel NE NERFINISHED

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: Jason Segel | Statement: [Rachel Jansen, createdBy, Jason Segel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jason Segel
Context triple: [Rachel Jansen, createdBy, Jason Segel]
  • A. Jason Segel chosen
    Jason Segel is an American actor, comedian, screenwriter, and producer best known for his roles in the sitcom "How I Met Your Mother" and films like "Forgetting Sarah Marshall."
  • B. Seth Rogen
    Seth Rogen is a Canadian actor, comedian, writer, producer, and director known for his distinctive laugh and roles in numerous hit comedy films such as "Superbad," "Pineapple Express," and "Knocked Up."
  • C. Luke Wilson
    Luke Wilson is an American actor known for his roles in films such as "The Royal Tenenbaums," "Old School," and "Legally Blonde."
  • D. Seth Green
    Seth Green is an American actor, comedian, and producer best known for his voice work on "Family Guy" and for creating and starring in the stop-motion series "Robot Chicken."
  • E. Jonah Hill
    Jonah Hill is an American actor, comedian, and filmmaker known for his roles in films such as Superbad, Moneyball, and The Wolf of Wall Street.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e59db848190b4272ecd2b690ffd completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15f78d8288190871d54db0a7f454b completed April 29, 2026, 1:31 a.m.
Created at: April 16, 2026, 8:52 p.m.