Triple

T3558283
Position Surface form Disambiguated ID Type / Status
Subject Donkey Kong E75272 entity
Predicate voiceActor P1507 FINISHED
Object Seth Rogen E90874 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: Seth Rogen | Statement: [Donkey Kong, voiceActor, Seth Rogen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seth Rogen
Context triple: [Donkey Kong, voiceActor, Seth Rogen]
  • A. Seth Rogen chosen
    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."
  • B. Jason Segel
    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."
  • C. 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."
  • D. 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.
  • E. Evan Goldberg
    Evan Goldberg is a technology entrepreneur best known for founding the cloud-based business software company NetSuite.
  • 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_69ad85d45090819086f34fb85d850a1e completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc086e6688190b90ae356e18b953e completed March 8, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bb9983f48190bda2749d93c74a8d completed March 13, 2026, 7:24 a.m.
Created at: March 8, 2026, 3:20 p.m.