Triple

T21899647
Position Surface form Disambiguated ID Type / Status
Subject Aldous Snow E540773 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: [Aldous Snow, createdBy, Jason Segel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jason Segel
Context triple: [Aldous Snow, 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_69e0c47b4e8c81908c8076eaa4c8e4f2 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f11fca2bf88190b2a5b912aa102513 completed April 28, 2026, 8:59 p.m.
Created at: April 16, 2026, 7:07 p.m.