Triple

T21614397
Position Surface form Disambiguated ID Type / Status
Subject Krieger E533395 entity
Predicate hasNotableBearer P458 FINISHED
Object Kevin Systrom 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: Kevin Systrom | Statement: [Krieger, hasNotableBearer, Kevin Systrom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kevin Systrom
Context triple: [Krieger, hasNotableBearer, Kevin Systrom]
  • A. Kevin Systrom chosen
    Kevin Systrom is an American entrepreneur and programmer best known as the co-founder and former CEO of the photo-sharing social media platform Instagram.
  • B. Scott Belsky
    Scott Belsky is an American entrepreneur, author, and investor best known as the co-founder of the creative platform Behance and as a longtime product leader at Adobe.
  • C. Evan Spiegel
    Evan Spiegel is an American entrepreneur best known as the co-founder and CEO of Snap Inc., the company behind Snapchat.
  • D. Biz Stone
    Biz Stone is an American entrepreneur and software developer best known as one of the co-founders of Twitter and a prominent figure in the social media industry.
  • E. Sean Parker
    Sean Parker is an American entrepreneur and investor best known as the co-founder of Napster and the first president of Facebook.
  • 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_69e0c46411108190bba0d4176dffc9f3 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef3ba9aca48190b5180eefd61a9fdc completed April 27, 2026, 10:34 a.m.
Created at: April 16, 2026, 6:33 p.m.