Triple

T16641465
Position Surface form Disambiguated ID Type / Status
Subject Oscar Tshiebwe E404347 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 Tshiebwe, givenName, Oscar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oscar
Context triple: [Oscar Tshiebwe, givenName, Oscar]
  • A. 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.
  • B. 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.
  • 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 NATO reporting name for a class of large, nuclear-powered guided-missile submarines originally built by the Soviet Navy and now operated by the Russian Navy.
  • E. 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.
  • 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_69d8838a41f08190b0c3f79c47df5078 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ad1a7748190aa9308d4e96c566c completed April 18, 2026, 12:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0084bb4cec819091d9b7b2a09248ee completed May 10, 2026, 1:14 p.m.
Created at: April 10, 2026, 5:18 a.m.