Triple

T14374844
Position Surface form Disambiguated ID Type / Status
Subject Mark Getty E356445 entity
Predicate employer P7 FINISHED
Object Getty Images E72304 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: Getty Images | Statement: [Mark Getty, employer, Getty Images]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Getty Images
Context triple: [Mark Getty, employer, Getty Images]
  • A. Getty Images chosen
    Getty Images is a leading global provider of stock photography, editorial imagery, video, and other visual content for media, advertising, and corporate clients.
  • B. Getty
    Getty is a prominent American surname most famously associated with oil tycoon J. Paul Getty and the wealthy Getty family.
  • C. iStockphoto
    iStockphoto is an online microstock photography marketplace offering royalty-free images, illustrations, video, and audio clips contributed by a global community of creators.
  • D. Flickr
    Flickr is an online photo and video hosting and sharing platform that became one of the earliest popular social media sites for photographers and casual users alike.
  • E. Photolibrary
    Photolibrary was a stock photography agency and image licensing company later incorporated into Getty Images’ global visual media portfolio.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de9007184c8190aebb003cb6548cc8 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bbf21a48190921e99685c7ef2b9 completed May 8, 2026, 3:42 a.m.
Created at: April 10, 2026, 1:16 a.m.