Triple

T19544052
Position Surface form Disambiguated ID Type / Status
Subject June Brown E488990 entity
Predicate appearedIn P795 FINISHED
Object Bean 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: Bean | Statement: [June Brown, appearedIn, Bean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bean
Context triple: [June Brown, appearedIn, Bean]
  • A. Bean
    Bean is a common English surname of Old English origin, associated with various notable individuals including the actor Sean Bean.
  • B. Bean
    Bean is a small village and civil parish in the borough of Dartford in north-west Kent, England.
  • C. Bean chosen
    Bean is a 1997 British-American comedy film based on Rowan Atkinson’s Mr. Bean character, following his chaotic misadventures in the United States.
  • D. Bean
    Bean is the famous jazz saxophonist Coleman Hawkins, a pioneering tenor sax player whose rich tone and improvisational style helped define early jazz.
  • E. Bean
    Bean is an Australian federal electoral division in the Australian Capital Territory, represented in the House of Representatives.
  • 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_69d8e8db5b6c8190984b61f91981f575 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e638750b288190aecdb0e18a1add62 completed April 20, 2026, 2:30 p.m.
Created at: April 10, 2026, 1:41 p.m.