Triple

T8218545
Position Surface form Disambiguated ID Type / Status
Subject Oscar Westover E191999 entity
Predicate givenName P17 FINISHED
Object Oscar E359307 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: Oscar | Statement: [Oscar Westover, givenName, Oscar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oscar
Context triple: [Oscar Westover, givenName, Oscar]
  • A. Oscar
    Oscar is the Allied reporting name for the Nakajima Ki-43, a Japanese World War II fighter aircraft used extensively by the Imperial Japanese Army Air Service.
  • B. Oscar
    The Oscar is a prestigious film industry award presented annually by the Academy of Motion Picture Arts and Sciences to honor outstanding cinematic achievements.
  • C. Oscar chosen
    Oscar is a masculine given name of Old English and Norse origin, commonly used in many European and English-speaking countries.
  • D. OSCAR
    OSCAR is the proprietary messaging protocol developed by AOL to power its real-time chat and presence services across products like AIM and ICQ.
  • E. Orson
    Orson is a masculine given name most famously associated with the American filmmaker and actor Orson Welles.
  • 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_69ca82c9a8ac81908b011c38698456e4 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb7770cee881908ade560d49427895 completed March 31, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccedfb6f608190aebfa720b56325e5 completed April 1, 2026, 10:05 a.m.
Created at: March 30, 2026, 5:45 p.m.