Triple

T10880633
Position Surface form Disambiguated ID Type / Status
Subject Pom Klementieff E256909 entity
Predicate name P16 FINISHED
Object Pom Klementieff E256909 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: Pom Klementieff | Statement: [Pom Klementieff, name, Pom Klementieff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pom Klementieff
Context triple: [Pom Klementieff, name, Pom Klementieff]
  • A. Pom Klementieff chosen
    Pom Klementieff is a French actress best known for playing Mantis in the Marvel Cinematic Universe films.
  • B. Nikita Dragun
    Nikita Dragun is a transgender beauty influencer, YouTuber, and entrepreneur known for her makeup content and cosmetics brand Dragun Beauty.
  • C. Svetlana Khodchenkova
    Svetlana Khodchenkova is a Russian film and television actress known internationally for roles in movies such as "Tinker Tailor Soldier Spy" and "The Wolverine."
  • D. Juliana Koo
    Juliana Koo was a Chinese-American diplomat and socialite known for her work with the United Nations and her prominent role in international society in the mid-20th century.
  • E. Alexis Mdivani
    Alexis Mdivani was a Georgian-born aristocrat and member of the socially prominent "Marrying Mdivanis," known for his high-profile marriage into great wealth and status.
  • 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_69d6aa848804819081b2713ca0bedf06 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d751b031a88190b1182dfc1f520264 completed April 9, 2026, 7:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7e2322c8190a55605237ae6ce95 completed April 15, 2026, 8:41 p.m.
Created at: April 8, 2026, 9:21 p.m.