Triple

T12370081
Position Surface form Disambiguated ID Type / Status
Subject Progressive GAN E294977 entity
Predicate introducedBy P513 FINISHED
Object Tero Karras E971754 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: Tero Karras | Statement: [Progressive GAN, introducedBy, Tero Karras]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tero Karras
Context triple: [Progressive GAN, introducedBy, Tero Karras]
  • A. Tero Karras chosen
    Tero Karras is a computer graphics and machine learning researcher known for pioneering work in generative adversarial networks, particularly the development of the StyleGAN architecture.
  • B. Pekka Rantala
    Pekka Rantala is a Finnish business executive best known for his leadership roles in the mobile phone industry, including co-founding HMD Global, the company behind modern Nokia-branded phones.
  • C. Taneli Kekkonen
    Taneli Kekkonen was a Finnish diplomat and the son of long-serving Finnish President Urho Kekkonen.
  • D. Ahti Rahkola
    Ahti Rahkola is a Finnish former javelin thrower who competed internationally during the 1970s and 1980s.
  • E. Jukka Kola
    Jukka Kola is a Finnish academic and university leader who serves as the rector of the University of Turku.
  • 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_69d6ab6d8a4081908636601e69ddf262 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93fa65a608190a1597a49751185a8 completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64b926c5c81909427eb191ae75ec6 completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:54 p.m.